{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FSRS4Anki Optimizer Power Forgetting Curve\n",
    "\n",
    "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/main/archive/candidate/power_forgetting_curve.ipynb)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are some settings that you need to replace before running this optimizer.\n",
    "\n",
    "filename = \"../collection-2022-09-18@13-21-58.colpkg\"\n",
    "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
    "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
    "\n",
    "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
    "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
    "timezone = 'Asia/Shanghai'\n",
    "\n",
    "# Replace it with your Anki's setting in Preferences -> Scheduling.\n",
    "next_day_starts_at = 4\n",
    "\n",
    "# Replace it if you don't want the optimizer to use the review logs before a specific date.\n",
    "revlog_start_date = \"2006-10-05\"\n",
    "\n",
    "# Set it to True if you don't want the optimizer to use the review logs from suspended cards.\n",
    "filter_out_suspended_cards = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import zipfile\n",
    "import sqlite3\n",
    "import time\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import math\n",
    "from typing import List, Optional\n",
    "from datetime import timedelta, datetime\n",
    "import statsmodels.api as sm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "import torch\n",
    "from torch import nn\n",
    "from torch import Tensor\n",
    "from torch.utils.data import Dataset, DataLoader, Sampler\n",
    "from torch.nn.utils.rnn import pad_sequence, pack_padded_sequence, pad_packed_sequence\n",
    "from sklearn.model_selection import StratifiedGroupKFold\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from itertools import accumulate\n",
    "from tqdm.auto import tqdm\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", category=UserWarning)\n",
    "tqdm.pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Deck file extracted successfully!\n",
      "revlog.csv saved.\n",
      "Trainset saved.\n",
      "Retention calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "91b82b4e48b84839b1a282c18844e37b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/26286 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Stability calculated.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "1a4775ec0bde4e08acc32793279763c0",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "analysis:   0%|          | 0/489 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Analysis saved!\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "      r_history  avg_interval  avg_retention  stability  factor  group_cnt\n",
      "              1           1.1          0.892        1.0     inf       2063\n",
      "            1,3           3.1          0.920        4.0    4.00       1600\n",
      "          1,3,3           7.1          0.910        7.9    1.98       1320\n",
      "        1,3,3,3          16.6          0.862       10.8    1.37        986\n",
      "      1,3,3,3,3          36.5          0.840       22.3    2.06        659\n",
      "    1,3,3,3,3,3          77.0          0.861       36.4    1.63        358\n",
      "  1,3,3,3,3,3,3         117.9          0.906       38.5    1.06        177\n",
      "              2           1.0          0.902        1.1     inf        240\n",
      "            2,3           3.5          0.946        8.2    7.45        201\n",
      "          2,3,3          11.4          0.890        7.6    0.93        162\n",
      "              3           1.1          0.977        5.0     inf       4669\n",
      "            3,3           3.3          0.967       12.0    2.40       4211\n",
      "          3,3,3           8.1          0.960       19.9    1.66       3757\n",
      "        3,3,3,3          18.3          0.941       41.5    2.09       2834\n",
      "      3,3,3,3,3          35.2          0.930       50.5    1.22       1761\n",
      "    3,3,3,3,3,3          64.9          0.929       97.9    1.94       1102\n",
      "  3,3,3,3,3,3,3         100.9          0.949      143.0    1.46        530\n",
      "3,3,3,3,3,3,3,3         133.6          0.990     1821.9   12.74        131\n",
      "              4           2.0          0.976       10.7     inf       2789\n",
      "            4,3           3.7          0.976       20.4    1.91       2293\n",
      "          4,3,3           8.3          0.967       32.5    1.59       2051\n",
      "        4,3,3,3          19.8          0.958       54.5    1.68       1700\n",
      "      4,3,3,3,3          41.0          0.958       99.5    1.83       1148\n",
      "    4,3,3,3,3,3          68.1          0.956      116.1    1.17        521\n",
      "  4,3,3,3,3,3,3          78.5          0.979      110.7    0.95        248\n",
      "4,3,3,3,3,3,3,3         114.1          0.984      177.8    1.61        166\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Step 1\"\"\"\n",
    "# Extract the collection file or deck file to get the .anki21 database.\n",
    "with zipfile.ZipFile(f'{filename}', 'r') as zip_ref:\n",
    "    zip_ref.extractall('./')\n",
    "    print(\"Deck file extracted successfully!\")\n",
    "\n",
    "\"\"\"Step 2\"\"\"\n",
    "if os.path.isfile(\"collection.anki21b\"):\n",
    "    os.remove(\"collection.anki21b\")\n",
    "    raise Exception(\n",
    "        \"Please export the file with `support older Anki versions` if you use the latest version of Anki.\")\n",
    "elif os.path.isfile(\"collection.anki21\"):\n",
    "    con = sqlite3.connect(\"collection.anki21\")\n",
    "elif os.path.isfile(\"collection.anki2\"):\n",
    "    con = sqlite3.connect(\"collection.anki2\")\n",
    "else:\n",
    "    raise Exception(\"Collection not exist!\")\n",
    "cur = con.cursor()\n",
    "res = cur.execute(f\"\"\"\n",
    "SELECT *\n",
    "FROM revlog\n",
    "WHERE cid IN (\n",
    "    SELECT id\n",
    "    FROM cards\n",
    "    {\"WHERE queue != -1\" if filter_out_suspended_cards else \"\"}\n",
    ")\n",
    "\"\"\"\n",
    ")\n",
    "revlog = res.fetchall()\n",
    "if len(revlog) == 0:\n",
    "    raise Exception(\"No review log found!\")\n",
    "df = pd.DataFrame(revlog)\n",
    "df.columns = ['id', 'cid', 'usn', 'r', 'ivl', 'last_lvl', 'factor', 'time', 'type']\n",
    "df = df[(df['cid'] <= time.time() * 1000) &\n",
    "        (df['id'] <= time.time() * 1000)].copy()\n",
    "\n",
    "df_set_due_date = df[(df['type'] == 4) & (df['ivl'] > 0)]\n",
    "df.drop(df_set_due_date.index, inplace=True)\n",
    "\n",
    "df['create_date'] = pd.to_datetime(df['cid'] // 1000, unit='s')\n",
    "df['create_date'] = df['create_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df['review_date'] = pd.to_datetime(df['id'] // 1000, unit='s')\n",
    "df['review_date'] = df['review_date'].dt.tz_localize('UTC').dt.tz_convert(timezone)\n",
    "df.drop(df[df['review_date'].dt.year < 2006].index, inplace=True)\n",
    "df.sort_values(by=['cid', 'id'], inplace=True, ignore_index=True)\n",
    "\n",
    "df['is_learn_start'] = (df['type'] == 0) & (df['type'].shift() != 0)\n",
    "df['sequence_group'] = df['is_learn_start'].cumsum()\n",
    "last_learn_start = df[df['is_learn_start']].groupby('cid')['sequence_group'].last()\n",
    "df['last_learn_start'] = df['cid'].map(last_learn_start).fillna(0).astype(int)\n",
    "df['mask'] = df['last_learn_start'] <= df['sequence_group']\n",
    "df = df[df['mask'] == True].copy()\n",
    "df.drop(columns=['is_learn_start', 'sequence_group', 'last_learn_start', 'mask'], inplace=True)\n",
    "df = df[(df['type'] != 4)].copy()\n",
    "\n",
    "type_sequence = np.array(df['type'])\n",
    "time_sequence = np.array(df['time'])\n",
    "df.to_csv(\"revlog.csv\", index=False)\n",
    "print(\"revlog.csv saved.\")\n",
    "\n",
    "df = df[(df['type'] != 3) | (df['factor'] != 0)].copy()\n",
    "df['real_days'] = df['review_date'] - timedelta(hours=int(next_day_starts_at))\n",
    "df['real_days'] = pd.DatetimeIndex(df['real_days'].dt.floor('D', ambiguous='infer', nonexistent='shift_forward')).to_julian_date()\n",
    "df.drop_duplicates(['cid', 'real_days'], keep='first', inplace=True)\n",
    "df['delta_t'] = df.real_days.diff()\n",
    "df.dropna(inplace=True)\n",
    "df['i'] = df.groupby('cid').cumcount() + 1\n",
    "df.loc[df['i'] == 1, 'delta_t'] = 0\n",
    "df = df.groupby('cid').filter(lambda group: group['type'].iloc[0] == 0)\n",
    "df['prev_type'] = df.groupby('cid')['type'].shift(1).fillna(0).astype(int)\n",
    "df['helper'] = ((df['type'] == 0) & ((df['prev_type'] == 1) | (df['prev_type'] == 2)) & (df['i'] > 1)).astype(int)\n",
    "df['helper'] = df.groupby('cid')['helper'].cumsum()\n",
    "df = df[df['helper'] == 0]\n",
    "del df['prev_type']\n",
    "del df['helper']\n",
    "\n",
    "def cum_concat(x):\n",
    "    return list(accumulate(x))\n",
    "\n",
    "t_history = df.groupby('cid', group_keys=False)['delta_t'].apply(lambda x: cum_concat([[int(i)] for i in x]))\n",
    "df['t_history']=[','.join(map(str, item[:-1])) for sublist in t_history for item in sublist]\n",
    "r_history = df.groupby('cid', group_keys=False)['r'].apply(lambda x: cum_concat([[i] for i in x]))\n",
    "df['r_history']=[','.join(map(str, item[:-1])) for sublist in r_history for item in sublist]\n",
    "df = df.groupby('cid').filter(lambda group: group['id'].min() > time.mktime(datetime.strptime(revlog_start_date, \"%Y-%m-%d\").timetuple()) * 1000)\n",
    "df['y'] = df['r'].map(lambda x: {1: 0, 2: 1, 3: 1, 4: 1}[x])\n",
    "df.to_csv('revlog_history.tsv', sep=\"\\t\", index=False)\n",
    "print(\"Trainset saved.\")\n",
    "\n",
    "df['retention'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['y'].transform('mean')\n",
    "df['total_cnt'] = df.groupby(by=['r_history', 'delta_t'], group_keys=False)['id'].transform('count')\n",
    "print(\"Retention calculated.\")\n",
    "\n",
    "df = df.drop(columns=['id', 'cid', 'usn', 'ivl', 'last_lvl', 'factor', 'time', 'type', 'create_date', 'review_date', 'real_days', 'r', 't_history', 'y'])\n",
    "df.drop_duplicates(inplace=True)\n",
    "df['retention'] = df['retention'].map(lambda x: max(min(0.99, x), 0.01))\n",
    "\n",
    "def cal_stability(group: pd.DataFrame) -> pd.DataFrame:\n",
    "    group_cnt = sum(group['total_cnt'])\n",
    "    if group_cnt < 10:\n",
    "        return pd.DataFrame()\n",
    "    group['group_cnt'] = group_cnt\n",
    "    if group['i'].values[0] > 1:\n",
    "        r_ivl_cnt = sum(group['delta_t'] * group['retention'].map(np.log) * pow(group['total_cnt'], 2))\n",
    "        ivl_ivl_cnt = sum(group['delta_t'].map(lambda x: x ** 2) * pow(group['total_cnt'], 2))\n",
    "        group['stability'] = round(np.log(0.9) / (r_ivl_cnt / ivl_ivl_cnt), 1)\n",
    "    else:\n",
    "        group['stability'] = 0.0\n",
    "    group['avg_retention'] = round(sum(group['retention'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 3)\n",
    "    group['avg_interval'] = round(sum(group['delta_t'] * pow(group['total_cnt'], 2)) / sum(pow(group['total_cnt'], 2)), 1)\n",
    "    del group['total_cnt']\n",
    "    del group['retention']\n",
    "    del group['delta_t']\n",
    "    return group\n",
    "\n",
    "df = df.groupby(by=['r_history'], group_keys=False).progress_apply(cal_stability)\n",
    "print(\"Stability calculated.\")\n",
    "df.reset_index(drop = True, inplace = True)\n",
    "df.drop_duplicates(inplace=True)\n",
    "df.sort_values(by=['r_history'], inplace=True, ignore_index=True)\n",
    "\n",
    "if df.shape[0] > 0:\n",
    "    for idx in tqdm(df.index, desc=\"analysis\"):\n",
    "        item = df.loc[idx]\n",
    "        index = df[(df['i'] == item['i'] + 1) & (df['r_history'].str.startswith(item['r_history']))].index\n",
    "        df.loc[index, 'last_stability'] = item['stability']\n",
    "    df['factor'] = round(df['stability'] / df['last_stability'], 2)\n",
    "    df = df[(df['i'] >= 2) & (df['group_cnt'] >= 100)].copy()\n",
    "    df['last_recall'] = df['r_history'].map(lambda x: x[-1])\n",
    "    df = df[df.groupby(['i', 'r_history'], group_keys=False)['group_cnt'].transform(max) == df['group_cnt']]\n",
    "    df.to_csv('./stability_for_analysis.tsv', sep='\\t', index=None)\n",
    "    print(\"Analysis saved!\")\n",
    "    caption = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "    analysis = df[df['r_history'].str.contains(r'^[1-4][^124]*$', regex=True)][['r_history', 'avg_interval', 'avg_retention', 'stability', 'factor', 'group_cnt']].to_string(index=False)\n",
    "    print(caption + analysis)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "init_w = [1, 1, 5, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2, -0.2, 0.2, 1]\n",
    "\n",
    "def power_forgetting_curve(t, s):\n",
    "    return (1 + t / (9 * s)) ** -1\n",
    "\n",
    "class FSRS(nn.Module):\n",
    "    def __init__(self, w: List[float]):\n",
    "        super(FSRS, self).__init__()\n",
    "        self.w = nn.Parameter(torch.tensor(w, dtype=torch.float32))\n",
    "\n",
    "    def stability_after_success(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = state[:,0] * (1 + torch.exp(self.w[6]) *\n",
    "                        (11 - new_d) *\n",
    "                        torch.pow(state[:,0], self.w[7]) *\n",
    "                        (torch.exp((1 - r) * self.w[8]) - 1))\n",
    "        return new_s\n",
    "\n",
    "    def stability_after_failure(self, state: Tensor, new_d: Tensor, r: Tensor) -> Tensor:\n",
    "        new_s = self.w[9] * torch.pow(new_d, self.w[10]) * torch.pow(\n",
    "            state[:,0], self.w[11]) * torch.exp((1 - r) * self.w[12])\n",
    "        return new_s\n",
    "\n",
    "    def step(self, X: Tensor, state: Tensor) -> Tensor:\n",
    "        '''\n",
    "        :param X: shape[batch_size, 2], X[:,0] is elapsed time, X[:,1] is rating\n",
    "        :param state: shape[batch_size, 2], state[:,0] is stability, state[:,1] is difficulty\n",
    "        :return state:\n",
    "        '''\n",
    "        if torch.equal(state, torch.zeros_like(state)):\n",
    "            # first learn, init memory states\n",
    "            new_s = self.w[0] + self.w[1] * (X[:,1] - 1)\n",
    "            new_d = self.w[2] + self.w[3] * (X[:,1] - 3)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "        else:\n",
    "            r = power_forgetting_curve(X[:,0], state[:,0])\n",
    "            new_d = state[:,1] + self.w[4] * (X[:,1] - 3)\n",
    "            new_d = self.mean_reversion(self.w[2], new_d)\n",
    "            new_d = new_d.clamp(1, 10)\n",
    "            condition = X[:,1] > 1\n",
    "            new_s = torch.where(condition, self.stability_after_success(state, new_d, r), self.stability_after_failure(state, new_d, r))\n",
    "        new_s = new_s.clamp(0.1, 36500)\n",
    "        return torch.stack([new_s, new_d], dim=1)\n",
    "\n",
    "    def forward(self, inputs: Tensor, state: Optional[Tensor]=None) -> Tensor:\n",
    "        '''\n",
    "        :param inputs: shape[seq_len, batch_size, 2]\n",
    "        '''\n",
    "        if state is None:\n",
    "            state = torch.zeros((inputs.shape[1], 2))\n",
    "        outputs = []\n",
    "        for X in inputs:\n",
    "            state = self.step(X, state)\n",
    "            outputs.append(state)\n",
    "        return torch.stack(outputs), state\n",
    "\n",
    "    def mean_reversion(self, init: Tensor, current: Tensor) -> Tensor:\n",
    "        return self.w[5] * init + (1-self.w[5]) * current\n",
    "\n",
    "class WeightClipper:\n",
    "    def __init__(self, frequency: int=1):\n",
    "        self.frequency = frequency\n",
    "\n",
    "    def __call__(self, module):\n",
    "        if hasattr(module, 'w'):\n",
    "            w = module.w.data\n",
    "            w[0] = w[0].clamp(0.1, 10)\n",
    "            w[1] = w[1].clamp(0.1, 5)\n",
    "            w[2] = w[2].clamp(1, 10)\n",
    "            w[3] = w[3].clamp(-5, -0.1)\n",
    "            w[4] = w[4].clamp(-5, -0.1)\n",
    "            w[5] = w[5].clamp(0.05, 0.5)\n",
    "            w[6] = w[6].clamp(0, 2)\n",
    "            w[7] = w[7].clamp(-0.8, -0.15)\n",
    "            w[8] = w[8].clamp(0.01, 1.5)\n",
    "            w[9] = w[9].clamp(0.5, 5)\n",
    "            w[10] = w[10].clamp(-2, -0.01)\n",
    "            w[11] = w[11].clamp(0.01, 0.9)\n",
    "            w[12] = w[12].clamp(0.01, 2)\n",
    "            module.w.data = w\n",
    "\n",
    "def lineToTensor(line: str) -> Tensor:\n",
    "    ivl = line[0].split(',')\n",
    "    response = line[1].split(',')\n",
    "    tensor = torch.zeros(len(response), 2)\n",
    "    for li, response in enumerate(response):\n",
    "        tensor[li][0] = int(ivl[li])\n",
    "        tensor[li][1] = int(response)\n",
    "    return tensor\n",
    "\n",
    "class RevlogDataset(Dataset):\n",
    "    def __init__(self, dataframe: pd.DataFrame):\n",
    "        if dataframe.empty:\n",
    "            raise ValueError('Training data is inadequate.')\n",
    "        padded = pad_sequence(dataframe['tensor'].to_list(), batch_first=True, padding_value=0)\n",
    "        self.x_train = padded.int()\n",
    "        self.t_train = torch.tensor(dataframe['delta_t'].values, dtype=torch.int)\n",
    "        self.y_train = torch.tensor(dataframe['y'].values, dtype=torch.float)\n",
    "        self.seq_len = torch.tensor(dataframe['tensor'].map(len).values, dtype=torch.long)\n",
    "\n",
    "    def __getitem__(self, idx):\n",
    "        return self.x_train[idx], self.t_train[idx], self.y_train[idx], self.seq_len[idx]\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.y_train)\n",
    "\n",
    "class RevlogSampler(Sampler[List[int]]):\n",
    "    def __init__(self, data_source: RevlogDataset, batch_size: int):\n",
    "        self.data_source = data_source\n",
    "        self.batch_size = batch_size\n",
    "        lengths = np.array(data_source.seq_len)\n",
    "        indices = np.argsort(lengths)\n",
    "        full_batches, remainder = divmod(indices.size, self.batch_size)\n",
    "        if full_batches > 0:\n",
    "            if remainder == 0:\n",
    "                self.batch_indices = np.split(indices, full_batches)\n",
    "            else:\n",
    "                self.batch_indices = np.split(indices[:-remainder], full_batches)\n",
    "        else:\n",
    "            self.batch_indices = []\n",
    "        if remainder > 0:\n",
    "            self.batch_indices.append(indices[-remainder:])\n",
    "        self.batch_nums = len(self.batch_indices)\n",
    "        # seed = int(torch.empty((), dtype=torch.int64).random_().item())\n",
    "        seed = 2023\n",
    "        self.generator = torch.Generator()\n",
    "        self.generator.manual_seed(seed)\n",
    "\n",
    "    def __iter__(self):\n",
    "        yield from (self.batch_indices[idx] for idx in torch.randperm(self.batch_nums, generator=self.generator).tolist())\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.data_source)\n",
    "\n",
    "\n",
    "def collate_fn(batch):\n",
    "    sequences, delta_ts, labels, seq_lens = zip(*batch)\n",
    "    sequences_packed = pack_padded_sequence(torch.stack(sequences, dim=1), lengths=torch.stack(seq_lens), batch_first=False, enforce_sorted=False)\n",
    "    sequences_padded, length = pad_packed_sequence(sequences_packed, batch_first=False)\n",
    "    sequences_padded = torch.as_tensor(sequences_padded)\n",
    "    seq_lens = torch.as_tensor(length)\n",
    "    delta_ts = torch.as_tensor(delta_ts)\n",
    "    labels = torch.as_tensor(labels)\n",
    "    return sequences_padded, delta_ts, labels, seq_lens\n",
    "\n",
    "class Trainer:\n",
    "    def __init__(self, train_set: pd.DataFrame, test_set: pd.DataFrame, init_w: List[float], n_epoch: int=1, lr: float=1e-2, batch_size: int=256) -> None:\n",
    "        self.model = FSRS(init_w)\n",
    "        self.optimizer = torch.optim.Adam(self.model.parameters(), lr=lr)\n",
    "        self.clipper = WeightClipper()\n",
    "        self.batch_size = batch_size\n",
    "        self.build_dataset(train_set, test_set)\n",
    "        self.n_epoch = n_epoch\n",
    "        self.batch_nums = self.next_train_data_loader.batch_sampler.batch_nums\n",
    "        self.scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(self.optimizer, T_max=self.batch_nums * n_epoch)\n",
    "        self.avg_train_losses = []\n",
    "        self.avg_eval_losses = []\n",
    "        self.loss_fn = nn.BCELoss(reduction='sum')\n",
    "\n",
    "    def build_dataset(self, train_set: pd.DataFrame, test_set: pd.DataFrame):\n",
    "        pre_train_set = train_set[train_set['i'] == 2]\n",
    "        self.pre_train_set = RevlogDataset(pre_train_set)\n",
    "        sampler = RevlogSampler(self.pre_train_set, batch_size=self.batch_size)\n",
    "        self.pre_train_data_loader = DataLoader(self.pre_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        next_train_set = train_set[train_set['i'] > 2]\n",
    "        self.next_train_set = RevlogDataset(next_train_set)\n",
    "        sampler = RevlogSampler(self.next_train_set, batch_size=self.batch_size)\n",
    "        self.next_train_data_loader = DataLoader(self.next_train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.train_set = RevlogDataset(train_set)\n",
    "        sampler = RevlogSampler(self.train_set, batch_size=self.batch_size)\n",
    "        self.train_data_loader = DataLoader(self.train_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "\n",
    "        self.test_set = RevlogDataset(test_set)\n",
    "        sampler = RevlogSampler(self.test_set, batch_size=self.batch_size)\n",
    "        self.test_data_loader = DataLoader(self.test_set, batch_sampler=sampler, collate_fn=collate_fn)\n",
    "        print(\"dataset built\")\n",
    "\n",
    "    def train(self, verbose: bool=True):\n",
    "        # pretrain\n",
    "        best_loss = np.inf\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        pbar = tqdm(desc=\"pre-train\", colour=\"red\", total=len(self.pre_train_data_loader) * self.n_epoch)\n",
    "        for k in range(self.n_epoch):\n",
    "            for i, batch in enumerate(self.pre_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = power_forgetting_curve(delta_ts, stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                self.optimizer.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(n=real_batch_size)\n",
    "\n",
    "        pbar.close()\n",
    "        for name, param in self.model.named_parameters():\n",
    "            tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "\n",
    "        epoch_len = len(self.next_train_data_loader)\n",
    "        pbar = tqdm(desc=\"train\", colour=\"red\", total=epoch_len*self.n_epoch)\n",
    "        print_len = max(self.batch_nums*self.n_epoch // 10, 1)\n",
    "        for k in range(self.n_epoch):\n",
    "            weighted_loss, w = self.eval()\n",
    "            if weighted_loss < best_loss:\n",
    "                best_loss = weighted_loss\n",
    "                best_w = w\n",
    "\n",
    "            for i, batch in enumerate(self.next_train_data_loader):\n",
    "                self.model.train()\n",
    "                self.optimizer.zero_grad()\n",
    "                sequences, delta_ts, labels, seq_lens = batch\n",
    "                real_batch_size = seq_lens.shape[0]\n",
    "                outputs, _ = self.model(sequences)\n",
    "                stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "                retentions = power_forgetting_curve(delta_ts, stabilities)\n",
    "                loss = self.loss_fn(retentions, labels)\n",
    "                loss.backward()\n",
    "                for param in self.model.parameters():\n",
    "                    param.grad[:2] = torch.zeros(2)\n",
    "                self.optimizer.step()\n",
    "                self.scheduler.step()\n",
    "                self.model.apply(self.clipper)\n",
    "                pbar.update(real_batch_size)\n",
    "\n",
    "                if verbose and (k * self.batch_nums + i + 1) % print_len == 0:\n",
    "                    tqdm.write(f\"iteration: {k * epoch_len + (i + 1) * self.batch_size}\")\n",
    "                    for name, param in self.model.named_parameters():\n",
    "                        tqdm.write(f\"{name}: {list(map(lambda x: round(float(x), 4),param))}\")\n",
    "        pbar.close()\n",
    "\n",
    "        weighted_loss, w = self.eval()\n",
    "        if weighted_loss < best_loss:\n",
    "            best_loss = weighted_loss\n",
    "            best_w = w\n",
    "\n",
    "        return best_w\n",
    "\n",
    "    def eval(self):\n",
    "        self.model.eval()\n",
    "        with torch.no_grad():\n",
    "            sequences, delta_ts, labels, seq_lens = self.train_set.x_train, self.train_set.t_train, self.train_set.y_train, self.train_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = power_forgetting_curve(delta_ts, stabilities)\n",
    "            tran_loss = self.loss_fn(retentions, labels)/len(self.train_set)\n",
    "            self.avg_train_losses.append(tran_loss)\n",
    "            tqdm.write(f\"Loss in trainset: {tran_loss:.4f}\")\n",
    "\n",
    "            sequences, delta_ts, labels, seq_lens = self.test_set.x_train, self.test_set.t_train, self.test_set.y_train, self.test_set.seq_len\n",
    "            real_batch_size = seq_lens.shape[0]\n",
    "            outputs, _ = self.model(sequences.transpose(0, 1))\n",
    "            stabilities = outputs[seq_lens-1, torch.arange(real_batch_size), 0]\n",
    "            retentions = power_forgetting_curve(delta_ts, stabilities)\n",
    "            test_loss = self.loss_fn(retentions, labels)/len(self.test_set)\n",
    "            self.avg_eval_losses.append(test_loss)\n",
    "            tqdm.write(f\"Loss in testset: {test_loss:.4f}\")\n",
    "\n",
    "            w = list(map(lambda x: round(float(x), 4), dict(self.model.named_parameters())['w'].data))\n",
    "\n",
    "            weighted_loss = (tran_loss * len(self.train_set) + test_loss * len(self.test_set)) / (len(self.train_set) + len(self.test_set))\n",
    "\n",
    "            return weighted_loss, w\n",
    "\n",
    "    def plot(self):\n",
    "        fig = plt.figure()\n",
    "        ax = fig.gca()\n",
    "        ax.plot(self.avg_train_losses, label='train')\n",
    "        ax.plot(self.avg_eval_losses, label='test')\n",
    "        ax.set_xlabel('epoch')\n",
    "        ax.set_ylabel('loss')\n",
    "        ax.legend()\n",
    "        return fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4728e2331a80482b863a3c36c3b89b05",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/88151 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensorized!\n",
      "TRAIN: 57372 TEST: 30779\n",
      "dataset built\n",
      "Loss in trainset: 0.3327\n",
      "Loss in testset: 0.3107\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "9c550313962643cb89fd3c1e2e1e4d4e",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/15276 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.1967, 1.8631, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7dc746e95f3d48198ef37f31da1b5981",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156840 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3304\n",
      "Loss in testset: 0.3085\n",
      "iteration: 15360\n",
      "w: [1.1672, 2.0748, 5.226, -1.3312, -1.108, 0.05, 1.4657, -0.15, 0.8813, 2.0461, -0.1677, 0.3384, 0.7857]\n",
      "iteration: 30720\n",
      "w: [1.1656, 2.0862, 5.349, -1.8791, -1.4281, 0.05, 1.4998, -0.15, 0.9057, 2.0688, -0.1618, 0.2728, 0.8089]\n",
      "iteration: 46080\n",
      "w: [1.1656, 2.0868, 5.1866, -1.8164, -1.5457, 0.05, 1.496, -0.1654, 0.9037, 2.0644, -0.1843, 0.3765, 0.7721]\n",
      "Loss in trainset: 0.3163\n",
      "Loss in testset: 0.2958\n",
      "iteration: 60984\n",
      "w: [1.1655, 2.0868, 5.185, -1.9316, -1.6618, 0.05, 1.4668, -0.2267, 0.8708, 1.9801, -0.2797, 0.3452, 0.7381]\n",
      "iteration: 76344\n",
      "w: [1.1655, 2.0868, 5.0044, -1.8826, -1.6467, 0.05, 1.5182, -0.1697, 0.9148, 2.0138, -0.2523, 0.2809, 0.7241]\n",
      "iteration: 91704\n",
      "w: [1.1655, 2.0868, 5.0765, -1.997, -1.7474, 0.05, 1.4622, -0.2322, 0.8606, 2.0596, -0.2125, 0.3003, 0.6477]\n",
      "Loss in trainset: 0.3159\n",
      "Loss in testset: 0.2955\n",
      "iteration: 106608\n",
      "w: [1.1655, 2.0868, 4.9842, -1.9691, -1.7287, 0.05, 1.4986, -0.1867, 0.8904, 2.0168, -0.2591, 0.3315, 0.5582]\n",
      "iteration: 121968\n",
      "w: [1.1655, 2.0868, 4.9743, -1.9682, -1.7464, 0.05, 1.4847, -0.1915, 0.8739, 2.0448, -0.2319, 0.351, 0.5596]\n",
      "iteration: 137328\n",
      "w: [1.1655, 2.0868, 4.9615, -1.9707, -1.7486, 0.05, 1.4851, -0.1812, 0.8722, 2.0419, -0.2356, 0.361, 0.5557]\n",
      "iteration: 152688\n",
      "w: [1.1655, 2.0868, 4.9612, -1.9693, -1.7499, 0.05, 1.479, -0.1878, 0.8658, 2.0357, -0.2418, 0.355, 0.5503]\n",
      "Loss in trainset: 0.3157\n",
      "Loss in testset: 0.2953\n",
      "TRAIN: 59696 TEST: 28455\n",
      "dataset built\n",
      "Loss in trainset: 0.3188\n",
      "Loss in testset: 0.3381\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ceb53d53d9bc4d3c97129959ee78988c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/22374 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [2.0404, 2.0717, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "acbe06b4df404865a4e03e3699a509ce",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156714 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3159\n",
      "Loss in testset: 0.3368\n",
      "iteration: 15360\n",
      "w: [2.1417, 2.185, 5.1482, -1.3189, -1.2389, 0.05, 1.5556, -0.15, 0.9776, 1.9657, -0.2654, 0.1851, 1.0349]\n",
      "iteration: 30720\n",
      "w: [2.1469, 2.1909, 5.2154, -1.8547, -1.4901, 0.05, 1.5024, -0.1941, 0.9627, 2.0152, -0.2426, 0.4026, 1.0405]\n",
      "iteration: 46080\n",
      "w: [2.1471, 2.1911, 5.0801, -2.0104, -1.4939, 0.05, 1.4585, -0.195, 0.9341, 1.9857, -0.2879, 0.3566, 0.9266]\n",
      "Loss in trainset: 0.3020\n",
      "Loss in testset: 0.3229\n",
      "iteration: 60942\n",
      "w: [2.1471, 2.1911, 5.101, -1.9802, -1.6966, 0.054, 1.3612, -0.2236, 0.8366, 2.0038, -0.2754, 0.3699, 0.8903]\n",
      "iteration: 76302\n",
      "w: [2.1471, 2.1911, 4.9859, -1.955, -1.7013, 0.05, 1.3599, -0.1947, 0.8395, 1.982, -0.304, 0.389, 0.794]\n",
      "iteration: 91662\n",
      "w: [2.1471, 2.1911, 4.8299, -1.8823, -1.6709, 0.05, 1.4113, -0.15, 0.8854, 1.9839, -0.3053, 0.3955, 0.7471]\n",
      "Loss in trainset: 0.3017\n",
      "Loss in testset: 0.3227\n",
      "iteration: 106524\n",
      "w: [2.1471, 2.1911, 4.8288, -1.9303, -1.6855, 0.05, 1.3754, -0.1829, 0.8431, 2.0042, -0.2848, 0.4098, 0.7271]\n",
      "iteration: 121884\n",
      "w: [2.1471, 2.1911, 4.8271, -1.9761, -1.7152, 0.05, 1.383, -0.1696, 0.8486, 2.0036, -0.2851, 0.4011, 0.691]\n",
      "iteration: 137244\n",
      "w: [2.1471, 2.1911, 4.8314, -1.9937, -1.7274, 0.05, 1.3775, -0.1674, 0.8413, 2.0081, -0.2807, 0.4037, 0.6895]\n",
      "iteration: 152604\n",
      "w: [2.1471, 2.1911, 4.8284, -1.9901, -1.728, 0.05, 1.3761, -0.1692, 0.8395, 2.005, -0.2837, 0.4009, 0.6854]\n",
      "Loss in trainset: 0.3017\n",
      "Loss in testset: 0.3226\n",
      "TRAIN: 59234 TEST: 28917\n",
      "dataset built\n",
      "Loss in trainset: 0.3239\n",
      "Loss in testset: 0.3275\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "cf44a4b24e5445c195b9afe7e51e600c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "pre-train:   0%|          | 0/20916 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "w: [1.2245, 1.8688, 5.0, -0.5, -0.5, 0.2, 1.4, -0.2, 0.8, 2.0, -0.2, 0.2, 1.0]\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "da56b4903b1b4e33a30127ac2e53f049",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "train:   0%|          | 0/156786 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loss in trainset: 0.3218\n",
      "Loss in testset: 0.3248\n",
      "iteration: 15360\n",
      "w: [1.1548, 1.9619, 5.2385, -1.3278, -1.2879, 0.05, 1.4608, -0.1715, 0.8999, 1.9768, -0.2205, 0.2864, 1.0059]\n",
      "iteration: 30720\n",
      "w: [1.1511, 1.9668, 5.2396, -1.5931, -1.5399, 0.05, 1.4099, -0.1546, 0.8577, 1.9236, -0.2795, 0.3583, 0.7161]\n",
      "iteration: 46080\n",
      "w: [1.151, 1.967, 5.1021, -1.8131, -1.5686, 0.05, 1.4375, -0.1503, 0.8695, 1.9911, -0.2294, 0.3359, 0.5691]\n",
      "Loss in trainset: 0.3082\n",
      "Loss in testset: 0.3103\n",
      "iteration: 60966\n",
      "w: [1.151, 1.967, 4.9775, -1.681, -1.6918, 0.05, 1.4128, -0.1876, 0.8348, 2.0068, -0.2293, 0.3448, 0.4665]\n",
      "iteration: 76326\n",
      "w: [1.151, 1.967, 4.8653, -1.7166, -1.6915, 0.05, 1.3918, -0.1926, 0.807, 2.0005, -0.2393, 0.319, 0.4515]\n",
      "iteration: 91686\n",
      "w: [1.151, 1.967, 4.8218, -1.8052, -1.7797, 0.05, 1.4536, -0.1562, 0.8623, 2.0464, -0.1925, 0.3448, 0.4081]\n",
      "Loss in trainset: 0.3080\n",
      "Loss in testset: 0.3100\n",
      "iteration: 106572\n",
      "w: [1.151, 1.967, 4.7955, -1.8651, -1.7797, 0.0538, 1.4598, -0.16, 0.8645, 2.026, -0.2155, 0.3377, 0.3405]\n",
      "iteration: 121932\n",
      "w: [1.151, 1.967, 4.7814, -1.8825, -1.7938, 0.05, 1.4465, -0.1791, 0.8489, 2.0158, -0.2262, 0.3403, 0.3154]\n",
      "iteration: 137292\n",
      "w: [1.151, 1.967, 4.7966, -1.9118, -1.8155, 0.05, 1.4348, -0.1849, 0.8359, 2.0267, -0.2153, 0.3525, 0.3137]\n",
      "iteration: 152652\n",
      "w: [1.151, 1.967, 4.7945, -1.9126, -1.8164, 0.05, 1.4335, -0.1857, 0.8342, 2.025, -0.2171, 0.3526, 0.3118]\n",
      "Loss in trainset: 0.3079\n",
      "Loss in testset: 0.3100\n",
      "\n",
      "Training finished!\n"
     ]
    },
    {
     "data": {
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oyLVFRUVVpstSj3h72nhzZCytGvmxL+cko95ZTe7JQrPLEhF3YrE4b3OZsV3EWm92u53i4mLX1127dmXDhg1ER0fTunXrEpufn9+prlm48soreeqpp1i7di12u51PPvmkzPOZwfRbbJUREBBAeno6a9as4R//+AeJiYksX768RJtrr72W9PR0fvjhB66//noGDx5MdnZ2pa85ceJEcnJyXNvu3bsvsRdSHwT72pmd0INGAV5syjzKve+mkl9k7g+9iEhVi46OZtWqVezYsYMDBw5w//33c+jQIYYNG8aaNWvYtm0bX331FQkJCRQXF7Nq1SqeeeYZfvrpJ3bt2sXChQvZv38/7dq1c51v3bp1ZGRkcODAAQoLa/4/l6YGpIYNG2Kz2cjKyiqxPysr67wTs6xWK61btyYmJoaHHnqIQYMGkZSUVKKNn58frVu35ne/+x1vvfUWHh4evPXWWwBEREScE5aKioo4dOhQudf18vIiMDCwxCZSEVEhvsxO6I6f3UbKrwf564frcDgq9u4QERF38PDDD2Oz2Wjfvj2NGjWioKCAlStXUlxcTN++fenYsSPjxo0jODgYq9VKYGAg3377LTfccAOXX345jz/+OC+99BJ/+MMfALjnnnto06YNsbGxNGrUiJUrV9Z4n0ydg2S32+nWrRvJyckMGDAAAIfDQXJyMmPGjKnweRwOR4n5QRdq07NnT44cOUJqairdunUD4JtvvsHhcBAXF1e5zoicR4fGQcy6oxsJ76zh8//tJTLIm4k3tDO7LBGRKnH55ZeXOXd44cKFZbZv164dixcvLvd8jRo14uuvv66y+irD9FtsiYmJ/Otf/2LOnDls3LiRv/zlL+Tl5ZGQkADAiBEjSkziTkpKYsmSJfz6669s3LiRl156iblz53L77bcDkJeXx9/+9jd+/PFHdu7cSWpqKnfeeSe//fYbf/rTnwDnC3P99ddzzz33sHr1alauXMmYMWMYOnQojRub9HZKqfP+77JGPD+oEwBvfPsrs1duN7kiEREpj+nrIA0ZMoT9+/czadIkMjMziYmJYfHixa6J27t27cJqPZPj8vLyuO+++9izZw8+Pj60bduWefPmMWTIEABsNhubNm1izpw5HDhwgNDQULp37853331Hhw4dXOd57733GDNmDNdddx1Wq5WBAwfy2muv1Wznpd65tWtT9uWc5IWvMnhq0S+EB3rzh46RZpclIiKlWAyjgktlSgm5ubkEBQWRk5Oj+UhyUQzD4InPfmbej7uwe1h57+44ukeHmF2WiJjs5MmTbN++nRYtWuDtrSVBLsX5vpcV/f1t+i02kfrGYrHw1E1X0Kd9OAVFDu6e8xNbs7WQpIhIbaKAJGICm9XCa0O70LVZMDknChn59hqyck+aXZaI1AK6sXPpquJ7qIAkYhIfu423RnanZUM/fjtyglHvrOGoFpIUqbc8PT0BOH78uMmVuL/T38PT39PKMH2Stkh91sDPzpw7e3DL6z+wcV8uf5mXxtujumP30P9dROobm81GcHCwa50+X19fLBexmrU4R46OHz9OdnY2wcHB2Gy2Sp9Lk7QrSZO0pSqt35PDkH+mcLygmFu6NOHlwZ31D6NIPWQYBpmZmRw5csTsUtxacHAwERERZf47WtHf3xpBEqkFOjYN4vXhXblrzk98svY3IoK8efT6tmaXJSI1zGKxEBkZSVhYmCkfr1EXeHp6XtLI0WkKSCK1RO82YTx7a0f++tE6Zi7fRuMgb+7oGW12WSJiApvNViW/5KXyNNFBpBb5U2wUD/W5HIBJn2/gqw2ZJlckIlI/KSCJ1DJjft+aYT2aYRjwwL/XkrrzkNkliYjUOwpIIrWMxWJhys0diG8XRn6Rg7vm/MS2/cfMLktEpF5RQBKphTxsVl4b1oXOUcEcOV7IyLdXk31UC0mKiNQUBSSRWsrX7sHbI2OJDvVlz+ETJLyzhmP5RWaXJSJSLyggidRiof5ezLmzBw397WzYm8tf5qVSWOwwuywRkTpPAUmklmse6sdbI7vj42njuy0HePTjdfqsJhGRaqaAJOIGOkcF8/rwrtisFham/cZLX282uyQRkTpNAUnETVzbNoxnbrkCgOnLtvLeqp0mVyQiUncpIIm4kSHdmzEu/jIAnvj0Z5b8kmVyRSIidZMCkoibefC6yxjaPQqHAWP/nUbarsNmlyQiUucoIIm4GYvFwt8HXMG1bRpxstDBXbPX8KsWkhQRqVIKSCJuyMNmZfptXenUNIjDxwsZ+c5q9h/NN7ssEZE6QwFJxE35eXnw9qjuNA/1ZfehE9w5ew15WkhSRKRKKCCJuLGG/l7MSehBiJ+d9b/lcP/7aVpIUkSkCiggibi56IZ+vDUyFm9PK8sz9vPYJ+u1kKSIyCVSQBKpA7o0a8CM27pitcAHP+3hlaVbzC5JRMStKSCJ1BHXtQvn7wM6AvBa8hb+vXqXyRWJiLgvBSSROuS2uGY88PvWADz+6c98s0kLSYqIVIYCkkgdM77P5fypW1OKHQb3v7eW9N1HzC5JRMTtKCCJ1DEWi4Vnbu3INZc34kRhMXfOXsOOA3lmlyUi4lYUkETqIE+bldeHd+WKJoEcyitg5DurOXBMC0mKiFSUApJIHXV6IcmmDXzYefA4d81ew/ECLSQpIlIRCkgidVhYgDdz7uxBA19P/rcnhzHvr6VIC0mKiFyQApJIHdeqkT9vjuyOl4eVbzZl88RnP2shSRGRC1BAEqkHujVvwLRhXbBa4N+rd/Na8lazSxIRqdUUkETqib4dInjq5isAeGXpZj5Ys9vkikREaq9aEZBmzJhBdHQ03t7exMXFsXr16nLbLly4kNjYWIKDg/Hz8yMmJoa5c+e6ni8sLOTRRx+lY8eO+Pn50bhxY0aMGMHevXtLnCc6OhqLxVJie/bZZ6utjyK1wR2/a87917YCYOIn61mWkW1yRSIitZPpAWnBggUkJiYyefJk0tLS6Ny5M/369SM7u+x/uENCQnjsscdISUlh3bp1JCQkkJCQwFdffQXA8ePHSUtL44knniAtLY2FCxeSkZHBTTfddM65nn76afbt2+faxo4dW619FakNHu7bhlu7Njm1kGQa6/YcMbskEZFax2KYPFszLi6O7t27M336dAAcDgdRUVGMHTuWCRMmVOgcXbt2pX///kyZMqXM59esWUOPHj3YuXMnzZo1A5wjSOPGjWPcuHEVukZ+fj75+WfWkcnNzSUqKoqcnBwCAwMrdA6R2qKgyMFdc9bw3ZYDNPS3s/AvV9Is1NfsskREql1ubi5BQUEX/P1t6ghSQUEBqampxMfHu/ZZrVbi4+NJSUm54PGGYZCcnExGRgZXX311ue1ycnKwWCwEBweX2P/ss88SGhpKly5deOGFFygqKn+NmKSkJIKCglxbVFTUhTsoUkvZPazMvL0b7SMDOXDMuZDkQS0kKSLiYmpAOnDgAMXFxYSHh5fYHx4eTmZmZrnH5eTk4O/vj91up3///kybNo0+ffqU2fbkyZM8+uijDBs2rERSfOCBB5g/fz7Lli3j3nvv5ZlnnuGRRx4p95oTJ04kJyfHte3erQmu4t78vTyYndCdJsE+bD+Qx11zfuJEQbHZZYmI1AoeZhdQGQEBAaSnp3Ps2DGSk5NJTEykZcuW9O7du0S7wsJCBg8ejGEYzJw5s8RziYmJrsedOnXCbrdz7733kpSUhJeX1znX9PLyKnO/iDsLC3QuJDlo1g+k7z7C2H+vZdbtXfGwmT49UUTEVKb+K9iwYUNsNhtZWVkl9mdlZREREVHucVarldatWxMTE8NDDz3EoEGDSEpKKtHmdDjauXMnS5YsueA8obi4OIqKitixY0el+yPijlqH+fPmiFi8PKws3ZjFpM83aCFJEan3TA1Idrudbt26kZyc7NrncDhITk6mZ8+eFT6Pw+EoMYH6dDjasmULS5cuJTQ09ILnSE9Px2q1EhYWdnGdEKkDYqNDeHVoFywWeH/VLmYs00KSIlK/mX6LLTExkZEjRxIbG0uPHj2YOnUqeXl5JCQkADBixAiaNGniGiFKSkoiNjaWVq1akZ+fz5dffsncuXNdt9AKCwsZNGgQaWlpLFq0iOLiYtd8ppCQEOx2OykpKaxatYprr72WgIAAUlJSGD9+PLfffjsNGjQw5xshYrLrr4jgyRs7MPnzDbz49WYignwY1K2p2WWJiJjC9IA0ZMgQ9u/fz6RJk8jMzCQmJobFixe7Jm7v2rULq/XMQFdeXh733Xcfe/bswcfHh7Zt2zJv3jyGDBkCwG+//cbnn38OQExMTIlrLVu2jN69e+Pl5cX8+fN58sknyc/Pp0WLFowfP77EvCSR+mhkr2j25pzgjRW/MuHjdYQFeHH15Y3MLktEpMaZvg6Su6roOgoi7sbhMEj8IJ1P0/fiZ7ex4N6eXNEkyOyyRESqhFusgyQitY/VauH5QZ25snUoeQXFJMxew+5Dx80uS0SkRikgicg5Ti8k2TYigP1H8xn5zmoO5xWYXZaISI1RQBKRMgV6ezLnzh40DvLm1/153DVnDScLtZCkiNQPCkgiUq7wUwtJBnp7kLbrCA/8ey3FDk1bFJG6TwFJRM7rsvAA3hzZHbuHla9/yeJJLSQpIvWAApKIXFCPFiFMHRKDxQJzf9zJzBXbzC5JRKRaKSCJSIXc0DGSJ/q3B+D5xRksTNtjckUiItVHAUlEKuzOq1pwz/+1AOCRj9bx/ZYDJlckIlI9FJBE5KJM/EM7buzcmCKHwZ/npbJhb47ZJYmIVDkFJBG5KFarhRf/1InftQzhWH4RCe+sYc9hLSQpInWLApKIXDQvDxtv3BFLm/AAso/mM/Lt1Rw5roUkRaTuUEASkUoJ8vFk9p3diQzyZtv+PO559yctJCkidYYCkohUWmSQD7MTehDg7cGaHYcZvyBdC0mKSJ2ggCQil6RNRAD/vCMWu83Kf3/OZMqiX7SQpIi4PQUkEblkPVuF8tLgzgDM/mEH//z2V5MrEhG5NApIIlIlbuzcmMf7twMg6b+b+Cz9N5MrEhGpPAUkEakyd/9fS+680rmQ5MMf/o8ftmohSRFxTwpIIlKlHu/fjv4dIyksNrh3biob9+WaXZKIyEVTQBKRKmW1WnhpcGd6tAjhaH4Ro95ZzW9HTphdlojIRVFAEpEq5+1p4193xHJ5uD9ZufmMens1OccLzS5LRKTCFJBEpFoE+XoyO6EH4YFebMk+xj1ztZCkiLgPBSQRqTaNg08tJOnlwerth3jow//h0EKSIuIGFJBEpFq1iwzkjTu64Wmz8MW6ffzjy41mlyQickEKSCJS7Xq1bsiLf3IuJPnW99t58zstJCkitZsCkojUiJtjmjDxD20B+PsXG/nP//aaXJGISPkUkESkxoy+uiWjekUD8NAH/yNl20FzCxIRKYcCkojUGIvFwhN/bM/1HSIoKHYweu5PZGQeNbssEZFzKCCJSI2yWS1MHRpDbPMGHD3pXEhyX44WkhSR2kUBSURqnLenjTdHxtKqkR/7ck4y6u015JzQQpIiUnsoIImIKYJ97cy5swdhAV5kZB3l3rk/kV+khSRFpHZQQBIR0zRt4Ms7Cd3x9/Lgx18P8fCH67SQpIjUCgpIImKqDo2DmHl7VzysFv7zv708u3iT2SWJiCggiYj5/u+yRjw/qBMA//z2V97+frvJFYlIfaeAJCK1wq1dm/LI9W0AmPLFL3y5fp/JFYlIfVYrAtKMGTOIjo7G29ubuLg4Vq9eXW7bhQsXEhsbS3BwMH5+fsTExDB37lzX84WFhTz66KN07NgRPz8/GjduzIgRI9i7t+SqvYcOHWL48OEEBgYSHBzMXXfdxbFjx6qtjyJyYX+5phV3/K45hgHjFqSzevshs0sSkXrK9IC0YMECEhMTmTx5MmlpaXTu3Jl+/fqRnZ1dZvuQkBAee+wxUlJSWLduHQkJCSQkJPDVV18BcPz4cdLS0njiiSdIS0tj4cKFZGRkcNNNN5U4z/Dhw9mwYQNLlixh0aJFfPvtt4wePbra+ysi5bNYLDx5Uwf6tg+noMjB3XPWsCVLC0mKSM2zGIZh6ltG4uLi6N69O9OnTwfA4XAQFRXF2LFjmTBhQoXO0bVrV/r378+UKVPKfH7NmjX06NGDnTt30qxZMzZu3Ej79u1Zs2YNsbGxACxevJgbbriBPXv20Lhx43POkZ+fT35+vuvr3NxcoqKiyMnJITAw8GK7LSLncbKwmNv+9SNpu47QJNiHhff1IjzQ2+yyRKQOyM3NJSgo6IK/v00dQSooKCA1NZX4+HjXPqvVSnx8PCkpKRc83jAMkpOTycjI4Oqrry63XU5ODhaLheDgYABSUlIIDg52hSOA+Ph4rFYrq1atKvMcSUlJBAUFubaoqKgK9lJELpa3p423RnanZSM/fjtygpFvryb3pBaSFJGaY2pAOnDgAMXFxYSHh5fYHx4eTmZmZrnH5eTk4O/vj91up3///kybNo0+ffqU2fbkyZM8+uijDBs2zJUUMzMzCQsLK9HOw8ODkJCQcq87ceJEcnJyXNvu3bsvpqsicpEa+NmZk9CDhv5ebMo8yl/mpVJQ5DC7LBGpJ0yfg1QZAQEBpKens2bNGv7xj3+QmJjI8uXLz2lXWFjI4MGDMQyDmTNnXtI1vby8CAwMLLGJSPWKCvFldkJ3/Ow2Vm49yCMf/U8LSYpIjTA1IDVs2BCbzUZWVlaJ/VlZWURERJR7nNVqpXXr1sTExPDQQw8xaNAgkpKSSrQ5HY527tzJkiVLSgSaiIiIcyaBFxUVcejQofNeV0Rq3hVNgnj99m54WC18mr6X57/KMLskEakHTA1Idrudbt26kZyc7NrncDhITk6mZ8+eFT6Pw+EoMYH6dDjasmULS5cuJTQ0tET7nj17cuTIEVJTU137vvnmGxwOB3FxcZfQIxGpDtdc3oikWzsCMGvFNub8sMPcgkSkzvMwu4DExERGjhxJbGwsPXr0YOrUqeTl5ZGQkADAiBEjaNKkiWuEKCkpidjYWFq1akV+fj5ffvklc+fOdd1CKywsZNCgQaSlpbFo0SKKi4td84pCQkKw2+20a9eO66+/nnvuuYdZs2ZRWFjImDFjGDp0aJnvYBMR8/0pNoqs3JO8+PVmnvzPBsIDvbj+ikizyxKROsr0gDRkyBD279/PpEmTyMzMJCYmhsWLF7smbu/atQur9cxAV15eHvfddx979uzBx8eHtm3bMm/ePIYMGQLAb7/9xueffw5ATExMiWstW7aM3r17A/Dee+8xZswYrrvuOqxWKwMHDuS1116r/g6LSKXdf21r9uac5P1Vu3hwfjrv3e1FbHSI2WWJSB1k+jpI7qqi6yiISNUqKnbw53mpLN2YTZCPJx//pRetw/zNLktE3IRbrIMkInKxPGxWpg3rSkxUMDknChn59mqyc0+aXZaI1DEKSCLidnzsNt4aGUt0qC+/HTnBqHfWcFQLSYpIFVJAEhG3FOrvxZw7e9DQ384v+3K57700LSQpIlVGAUlE3FbzUD/eHtUdX7uN77YcYMLCdWhapYhUBQUkEXFrnZoGM2N4V2xWCwvTfuPFr7WQpIhcOgUkEXF717YJI+kW50KSM5ZtY+6PO02uSETcnQKSiNQJg7tHMS7+MgAmf/YzX28o/wOvRUQuRAFJROqMB6+7jKHdo3AYMPbfa0ndedjskkTETSkgiUidYbFY+PuAK/h92zDyixzcPWcNv+4/ZnZZIuKGFJBEpE7xsFmZflsXOjcN4vDxQka+s5rso1pIUkQujgKSiNQ5vnYP3hrVneahvuw+dII7Z6/hWH6R2WWJiBtRQBKROqmhvxdzEnoQ6mfn59+cC0kWFmshSRGpGAUkEamzohv68dao7vh42vh2834mLlyvhSRFpEIUkESkTouJCmb6bV2wWuCj1D28smSz2SWJiBtQQBKROu+6duH849RCkq99s5X3V+0yuSIRqe0UkESkXhjWoxkP/L41AI9/up7kjVkmVyQitZkCkojUG+P7XM6fujXFYcD976exdpcWkhSRsikgiUi9YbFYeObWjlxzeSNOFjq4a85PbD+QZ3ZZIlILKSCJSL3iabPy+vCudGwSxKG8Aka9s5oDx/LNLktEahkFJBGpd/y8PHh7VHeiQnzYefA4d85eQ54WkhSRsyggiUi91CjAuZBkA19P1u3JYcz7aRRpIUkROUUBSUTqrZaN/HlrVHe8Pa0sy9jPY5/8rIUkRQRQQBKReq5rswZMG9YVqwUW/LSbV5O3mF2SiNQCCkgiUu/1aR/O0zdfAcDUpVtYsEYLSYrUdx5mFyAiUhvc/rvm7Ms5wYxl2/jbJz+zNfsYgd6e2D2seHlYsXvYsHtYz/raipft9NfnPmf3sGK3Ob+2WCxmd09ELpICkojIKQ/3bcO+nJMsTPuNf323vcrOa7dZzw1QttKByuYMVJ5nglfJ9rZzAphXqee9PK1lXsvLdibA2awKayIVoYAkInKKxWLhuYGd6NQkiO0H8sgvclBQ5CC/+NSfRQ4KioopKHJQUOwgv9D5Z0HR2c87952toPjUvlqw3JKH1VJOWLOdCVSnR788zw5ytpIjY55nRshKPH9O8Dsd5M593sOmWR5SeykgiYicxdNmZdSVLS7pHIZhOANU0ZnwVDJAFZNfVPL5M4+Lzwlf+aXCV0FRcclzl9n+TJA7+415RQ6DooJijhcUX+J36tJZLZwVuGylAtfZActW9ijcqducp48t/byH1YqnzYKHzYqn1fmnh82Cp/XUnzYLHqce223Wc573sFp0e7QeU0ASEaliFosFLw8bXh42s0vBMAyKHEYZYe1UyCouHdBOBbjyAlqp8FX62PxiB/mFxeWOrBU7zqQ1hwEnCx2cLHTAydq5UKeH1VIyNJUTtk7v9zy932bF46yvz4Q1ywWDW8XPVXL/mePPDoFWPG26tVoZCkgiInWYxeIcKfG0WcHL7GqgqPjc25IlR8fOCmBnjY7lF5cR0MocPTszulbkMCgqdlBYbFDkcFBUbFB4+s/T+4sdFJ5q5yhjCawihzNgnsS9FxG1WCgxMlbxsHU6xDkf20+187BZXSNwZQW/85/L6vo7Wfa5zhzfwM/TtP9oKCCJiEiN8Th1K8vXbnYl53I4zgSo0mGqdNg6Ha6KHM7bqUWlwtaFjnfuL3muwnOOv5hznd5vnDMHDsAwTs+FM+EbewlmJ3Snd5swU66tgCQiIgJYrRa8rDa83Pw3o2EYFJ8a+SosFbAuJmy5ji0n+J0dCMsKfqXPVXie4FdeuPQ0cSK/m/81EBERkbNZLKdviYG3p/nz4NyV6e+xnDFjBtHR0Xh7exMXF8fq1avLbbtw4UJiY2MJDg7Gz8+PmJgY5s6de06bvn37EhoaisViIT09/Zzz9O7dG4vFUmL785//XNVdExERETdlakBasGABiYmJTJ48mbS0NDp37ky/fv3Izs4us31ISAiPPfYYKSkprFu3joSEBBISEvjqq69cbfLy8rjqqqt47rnnznvte+65h3379rm2559/vkr7JiIiIu7LYpj40dVxcXF0796d6dOnA+BwOIiKimLs2LFMmDChQufo2rUr/fv3Z8qUKSX279ixgxYtWrB27VpiYmJKPNe7d29iYmKYOnVqpWvPzc0lKCiInJwcAgMDK30eERERqTkV/f1t2ghSQUEBqampxMfHnynGaiU+Pp6UlJQLHm8YBsnJyWRkZHD11Vdf9PXfe+89GjZsyBVXXMHEiRM5fvz4edvn5+eTm5tbYhMREZG6qVIBac6cOXzxxReurx955BGCg4Pp1asXO3furNA5Dhw4QHFxMeHh4SX2h4eHk5mZWe5xOTk5+Pv7Y7fb6d+/P9OmTaNPnz4XVf9tt93GvHnzWLZsGRMnTmTu3Lncfvvt5z0mKSmJoKAg1xYVFXVR1xQRERH3UamA9Mwzz+Dj4wNASkoKM2bM4Pnnn6dhw4aMHz++SgssLSAggPT0dNasWcM//vEPEhMTWb58+UWdY/To0fTr14+OHTsyfPhw3n33XT755BO2bdtW7jETJ04kJyfHte3evfsSeyIiIiK1VaXe5r97925at24NwKeffsrAgQMZPXo0V155Jb17967QORo2bIjNZiMrK6vE/qysLCIiIso9zmq1uq4dExPDxo0bSUpKqvB1yxIXFwfA1q1badWqVZltvLy88PKqBcvQioiISLWr1AiSv78/Bw8eBODrr7923eLy9vbmxIkTFTqH3W6nW7duJCcnu/Y5HA6Sk5Pp2bNnhWtxOBzk51/aR2SfXgogMjLyks4jIiIidUOlRpD69OnD3XffTZcuXdi8eTM33HADABs2bCA6OrrC50lMTGTkyJHExsbSo0cPpk6dSl5eHgkJCQCMGDGCJk2akJSUBDjnAcXGxtKqVSvy8/P58ssvmTt3LjNnznSd89ChQ+zatYu9e/cCkJGRAUBERAQRERFs27aN999/nxtuuIHQ0FDWrVvH+PHjufrqq+nUqVNlvh0iIiJSx1QqIM2YMYPHH3+c3bt38/HHHxMaGgpAamoqw4YNq/B5hgwZwv79+5k0aRKZmZnExMSwePFi18TtXbt2YbWeGeTKy8vjvvvuY8+ePfj4+NC2bVvmzZvHkCFDXG0+//xzV8ACGDp0KACTJ0/mySefxG63s3TpUlcYi4qKYuDAgTz++OOV+VaIiIhIHWTqOkjuTOsgiYiIuJ9qXQdp8eLFfP/9966vZ8yYQUxMDLfddhuHDx+uzClFREREao1KBaS//vWvroUS169fz0MPPcQNN9zA9u3bSUxMrNICRURERGpapeYgbd++nfbt2wPw8ccf88c//pFnnnmGtLQ014RtEREREXdVqREku93u+miOpUuX0rdvX8D5YbL6CA4RERFxd5UaQbrqqqtITEzkyiuvZPXq1SxYsACAzZs307Rp0yotUERERKSmVWoEafr06Xh4ePDRRx8xc+ZMmjRpAsB///tfrr/++iotUERERKSm6W3+laS3+YuIiLifiv7+rtQtNoDi4mI+/fRTNm7cCECHDh246aabsNlslT2liIiISK1QqYC0detWbrjhBn777TfatGkDOD8GJCoqii+++KLcD3wVERERcQeVmoP0wAMP0KpVK3bv3k1aWhppaWns2rWLFi1a8MADD1R1jSIiIiI1qlIjSCtWrODHH38kJCTEtS80NJRnn32WK6+8ssqKExERETFDpUaQvLy8OHr06Dn7jx07ht1uv+SiRERERMxUqYD0xz/+kdGjR7Nq1SoMw8AwDH788Uf+/Oc/c9NNN1V1jSIiIiI1qlIB6bXXXqNVq1b07NkTb29vvL296dWrF61bt2bq1KlVXKKIiIhIzarUHKTg4GA+++wztm7d6nqbf7t27WjdunWVFiciIiJihgoHpMTExPM+v2zZMtfjl19+ufIViYiIiJiswgFp7dq1FWpnsVgqXYyIiIhIbVDhgHT2CJGIiIhIXVapSdoiIiIidZkCkoiIiEgpCkgiIiIipSggiYiIiJSigCQiIiJSigKSiIiISCkKSCIiIiKlKCCJiIiIlKKAJCIiIlKKApKIiIhIKQpIIiIiIqUoINU2hmF2BSIiIvVehT+sVmrIfx6AnSkQ3h7COkB4B+fj4GiwKs+KiIjUBAWk2iZzPRzc4tx++ezMfk8/CGvnDEvhV0BYe2d48g0xr1YREZE6SgGpthm2ALJ+huxfIOsX5+P9GVCYB7/95NzOFhB5KiydFZwatQEPL3PqFxERqQMshqFJL5WRm5tLUFAQOTk5BAYGVu/Fiovg0DbI2nAqOG1wbkd2lt3eYoOGl50ZZTq9BUWBxVK9tYqIiNRiFf39bfqklhkzZhAdHY23tzdxcXGsXr263LYLFy4kNjaW4OBg/Pz8iImJYe7cuee06du3L6GhoVgsFtLT0885z8mTJ7n//vsJDQ3F39+fgQMHkpWVVdVdqzo2D+eo0BW3wu8fh2H/hnHrYOIeuGsJ/HEqdL8Hml8J3sFgFMP+TbBhIXwzBf49FKZ2hGebwVt9YdF4WP0v2PkDnDhicudERERqH1NvsS1YsIDExERmzZpFXFwcU6dOpV+/fmRkZBAWFnZO+5CQEB577DHatm2L3W5n0aJFJCQkEBYWRr9+/QDIy8vjqquuYvDgwdxzzz1lXnf8+PF88cUXfPjhhwQFBTFmzBhuvfVWVq5cWa39rXJeARDVw7mdZhiQu7fkSFP2L87bdPm5sHuVcztbYNMzk8FPTwxveBnYPGu2PyIiIrWEqbfY4uLi6N69O9OnTwfA4XAQFRXF2LFjmTBhQoXO0bVrV/r378+UKVNK7N+xYwctWrRg7dq1xMTEuPbn5OTQqFEj3n//fQYNGgTApk2baNeuHSkpKfzud7+r0HVr9BZbVSguhANbTgWnn53zm7J/gZzdZbe3ejpHrUrPbwpsrNt0IiLitir6+9u0EaSCggJSU1OZOHGia5/VaiU+Pp6UlJQLHm8YBt988w0ZGRk899xzFb5uamoqhYWFxMfHu/a1bduWZs2anTcg5efnk5+f7/o6Nze3wtesFWyep4JOe+g46Mz+E0cge2OpieEboODoqSD1M6w/6zzewc4RphLBqZ1zNEtERKSOMC0gHThwgOLiYsLDw0vsDw8PZ9OmTeUel5OTQ5MmTcjPz8dms/H666/Tp0+fCl83MzMTu91OcHDwOdfNzMws97ikpCSeeuqpCl/HbfgEQ/Oezu00w3COLJ19iy5rg3ME6uQR2LnSuZ0tuPlZwenUbbqQVs75UyIiIm7G7X57BQQEkJ6ezrFjx0hOTiYxMZGWLVvSu3fvar3uxIkTSUxMdH2dm5tLVFRUtV7TNBYLBDdzbm3+cGZ/UT4c2HxucDq6z/mOuiM7IePLM+1tXs7bdKcD0+nw5B+u23QiIlKrmRaQGjZsiM1mO+fdY1lZWURERJR7nNVqpXXr1gDExMSwceNGkpKSKhyQIiIiKCgo4MiRIyVGkS50XS8vL7y86vnaQh5eENHRuZ3t+KFzlyDI3uhcuylznXM7m2/oqbB0xZmJ4WFtwe5Xc30RERE5D9MCkt1up1u3biQnJzNgwADAOUk7OTmZMWPGVPg8DoejxNygC+nWrRuenp4kJyczcOBAADIyMti1axc9e/a8wNFSJt8QaPF/zu00hwOO7DgzGfz0xPBD2+D4QdjxnXNzsUBIi1MjTR3OzG9qEA1WWw13SERE6jtTb7ElJiYycuRIYmNj6dGjB1OnTiUvL4+EhAQARowYQZMmTUhKSgKc84BiY2Np1aoV+fn5fPnll8ydO5eZM2e6znno0CF27drF3r17AWf4AefIUUREBEFBQdx1110kJiYSEhJCYGAgY8eOpWfPnhV+B5tUgNUKIS2dW7s/ntlfeMK5RtPpyeDZG5yP87Lh0K/ObeN/zrT38HGOLrmC06nNr2HN90lEROoNUwPSkCFD2L9/P5MmTSIzM5OYmBgWL17smri9a9curGd9QGteXh733Xcfe/bswcfHh7Zt2zJv3jyGDBniavP555+7AhbA0KFDAZg8eTJPPvkkAK+88gpWq5WBAweSn59Pv379eP3112ugx4KnDzTu4tzOdmz/mbB0Ojhlb4SiE7B3rXM7m19YyVXCw9pDo7bg6V1zfRERkTpLHzVSSW63DpI7chTDoe2ngtNZE8MPbQfK+GtrsUJo65LvpAtr73yHndX0ReNFRKQWqOjvbwWkSlJAMlFBHmRvOmvtplPh6cShstvb/Z1rNZWYGN7eOXdKRETqlVq/UKRIpdn9oGk353aaYcCxrJKrhGf97PyIlYJjsGeNcztbQONTk8HPmhje8HLnu/VERKRe0whSJWkEyU0UFznfOVc6OB3ZVXZ7qweEXlYqOHWAoKZau0lEpA7QLbZqpoDk5k7mOieBl54YfjKn7PZeQc7bdOEdSn7EindQzdYtIiKXRAGpmikg1UGGAbm/nRppOj0x/Bfn6uGOwrKPCYo69yNWQls7P/tORERqHQWkaqaAVI8UFcDBLadGms76UN/cPWW3t9mh5bVw6xvg06BmaxURkfNSQKpmCkjCicPO23QlPpvuFyg46ny+cVe44xPnBwKLiEitoHexiVQ3nwbQvJdzO80w4LdUeO9PsDcN5g10hiRvhWgREXei1fNEqpLFAk1jYeTnzgD120/OkJR/1OzKRETkIiggiVSHiI4w4jPwDoY9q2HeIIUkERE3ooAkUl0iO8OIT51LAez+Ed4bDPnHzK5KREQqQAFJpDo17uKcg+QVBLt+gPeHOD8qRUREajUFJJHq1qQb3LEQvAJh5/enQtJxs6sSEZHzUEASqQlNY+H2hWAPgB3fwb+HQuEJs6sSEZFyKCCJ1JSo7nD7x2D3h+0r4N/DFJJERGopBSSRmtQsDoZ/BJ5+8OsymD8cCk+aXZWIiJSigCRS05r3hOEfgqcvbEuGD+6AonyzqxIRkbMoIImYIfpKuO0D8PCBLV/DByMUkkREahEFJBGztPg/uG0+eHjD5sXw4SjnB+OKiIjpFJBEzNSyNwz7N9i8IONL+CgBigvNrkpEpN5TQBIxW6vfw7D3nSFp0yL46E6FJBERkykgidQGreNh6Htgs8PGz+Hju6G4yOyqRETqLQUkkdrisj4wZB5YPeGXT2HhPQpJIiImUUASqU0u7wdD5jpD0oaF8OmfwVFsdlUiIvWOApJIbdPmDzB4Dlg9YP2H8OlfFJJERGqYApJIbdS2Pwx6Byw2WLcAPhujkCQiUoMUkERqq/Y3waC3nSHpf+/D5w+Aw2F2VSIi9YICkkht1mEADPwXWKyQPg8WPaiQJCJSAxSQRGq7KwbCradCUtq78MV4hSQRkWqmgCTiDjoOggGzAAukzoYvHwbDMLsqEZE6SwFJxF10HgIDZgIW+Okt+PKvCkkiItVEAUnEncQMg5tnABZY8y9YPEEhSUSkGiggibibLsPhpmnOx6tmwVePKSSJiFQxBSQRd9T1DrjxVefjH2fAkicUkkREqlCtCEgzZswgOjoab29v4uLiWL16dbltFy5cSGxsLMHBwfj5+RETE8PcuXNLtDEMg0mTJhEZGYmPjw/x8fFs2bKlRJvo6GgsFkuJ7dlnn62W/olUi26joP/Lzsc/TIOlTyokiYhUEdMD0oIFC0hMTGTy5MmkpaXRuXNn+vXrR3Z2dpntQ0JCeOyxx0hJSWHdunUkJCSQkJDAV1995Wrz/PPP89prrzFr1ixWrVqFn58f/fr14+TJkyXO9fTTT7Nv3z7XNnbs2Grtq0iV634X3PCi8/HKqfDNFIUkEZEqYDEMc/81jYuLo3v37kyfPh0Ah8NBVFQUY8eOZcKECRU6R9euXenfvz9TpkzBMAwaN27MQw89xMMPPwxATk4O4eHhzJ49m6FDhwLOEaRx48Yxbty4StWdm5tLUFAQOTk5BAYGVuocIlVm1Rvw30ecj69+BH7/mLn1iIjUUhX9/W3qCFJBQQGpqanEx8e79lmtVuLj40lJSbng8YZhkJycTEZGBldffTUA27dvJzMzs8Q5g4KCiIuLO+eczz77LKGhoXTp0oUXXniBoqKicq+Vn59Pbm5uiU2k1oi7F/olOR9/+zws1+1iEZFL4WHmxQ8cOEBxcTHh4eEl9oeHh7Np06Zyj8vJyaFJkybk5+djs9l4/fXX6dOnDwCZmZmuc5Q+5+nnAB544AG6du1KSEgIP/zwAxMnTmTfvn28/PLLZV4zKSmJp556qlL9FKkRPe8Doxi+fhyWJzlX3r7mEbOrEhFxS6YGpMoKCAggPT2dY8eOkZycTGJiIi1btqR3794VPkdiYqLrcadOnbDb7dx7770kJSXh5eV1TvuJEyeWOCY3N5eoqKhL6odIles1FhzFsHQyLPuHMyRd/bDZVYmIuB1TA1LDhg2x2WxkZWWV2J+VlUVERES5x1mtVlq3bg1ATEwMGzduJCkpid69e7uOy8rKIjIyssQ5Y2Jiyj1nXFwcRUVF7NixgzZt2pzzvJeXV5nBSaTWuWocGA5Ifso5adtqg6vGm12ViIhbMXUOkt1up1u3biQnJ7v2ORwOkpOT6dmzZ4XP43A4yM/PB6BFixZERESUOGdubi6rVq067znT09OxWq2EhYVVoicitcz/JcLvH3c+XvokrHzN1HJERNyN6bfYEhMTGTlyJLGxsfTo0YOpU6eSl5dHQkICACNGjKBJkyYkJTknoCYlJREbG0urVq3Iz8/nyy+/ZO7cucycORMAi8XCuHHj+Pvf/85ll11GixYteOKJJ2jcuDEDBgwAICUlhVWrVnHttdcSEBBASkoK48eP5/bbb6dBgwamfB9EqtzVfwWHA5Y/41xI0mqDnvebXZWIiFswPSANGTKE/fv3M2nSJDIzM4mJiWHx4sWuSda7du3Caj0z0JWXl8d9993Hnj178PHxoW3btsybN48hQ4a42jzyyCPk5eUxevRojhw5wlVXXcXixYvx9vYGnLfL5s+fz5NPPkl+fj4tWrRg/PjxJeYYidQJvR91Ttxe8Rx89TfnnKTf/cXsqkREaj3T10FyV1oHSdyGYcA3f4fvTi0o+YcXIG60uTWJiJjELdZBEpEaYLE45yOdnqj937/CmjfNrUlEpJZTQBKpDywWuG4y9HrA+fUXD8FPb5tbk4hILaaAJFJfWCzQ52noOcb59aLxkDrb1JJERGorBSSR+sRigb5/h7hTE7X/8yCkzTW3JhGRWkgBSaS+sVjg+iToca/z68/HQvr75tYkIlLLKCCJ1EcWC/zhOeh+D2DAp/fB/+abXZWISK2hgCRSX1kscMMLEHsnzpD0F1j3odlViYjUCgpIIvWZxQI3vARdRzo/v+2T0bD+I7OrEhExnQKSSH1ntcIfp0KXO5whaeFo2PCJ2VWJiJhKAUlEnCHpxtcgZrjzo0k+ugt++czsqkRETKOAJCJOVivcNA06DT0Vku6Ejf8xuyoREVMoIInIGVYbDHgdOg4GRxF8OAo2fWF2VSIiNU4BSURKstpgwEy4YqAzJH0wEjL+a3ZVIiI1SgFJRM5l84Bb/gkdbgFHIXwwAjZ/bXZVIiI1RgFJRMpm84Bb34T2N0NxASwYDluWml2ViEiNUEASkfLZPGDgW9DuRmdImn8bbE02uyoRkWqngCQi52fzhIFvQ5v+UJzvDEnblpldlYhItVJAEpEL87DDn2bD5X+AopPw72Hw6wqzqxIRqTYKSCJSMR52GDwHLusHRSfg/SGw/TuzqxIRqRYKSCJScR5eMPhdaB1/KiQNhh0rza5KRKTKKSCJyMXx9IYh70Gr30PhcXjvT7AzxeyqRESqlAKSiFw8T28Y+j607A2FefDeINi1yuyqRESqjAKSiFSOpw8M/Te0uBoKjsG8gbB7jdlViYhUCQUkEak8uy8Mmw/R/wcFR2HerbAn1eyqREQumQKSiFwaux/ctgCaXwn5uTD3FvgtzeyqREQuiQKSiFw6ux/c9gE06wn5OTB3AOxNN7sqEZFKU0ASkarh5Q/DP4SoODiZA+/eDPvWmV2ViEilKCCJSNXxCoDhH0HT7nDyCLx7E2SuN7sqEZGLpoAkIlXLOxBu/xiadIMTh2HOTZC1weyqREQuigKSiFQ97yC4fSE07gInDjlDUvZGs6sSEakwBSQRqR4+wXDHJxDZGY4fgDk3QvYms6sSEakQBSQRqT4+DeCOTyGiI+Ttd4ak/ZvNrkpE5IIUkESkevmGwIjPIbwj5GU7Q9KBrWZXJSJyXgpIIlL9fENgxGcQ1gGOZcKcP8LBbWZXJSJSrloRkGbMmEF0dDTe3t7ExcWxevXqctsuXLiQ2NhYgoOD8fPzIyYmhrlz55ZoYxgGkyZNIjIyEh8fH+Lj49myZUuJNocOHWL48OEEBgYSHBzMXXfdxbFjx6qlfyIC+IXCyM+hUTs4ug9m/xEO/Wp2VSIiZTI9IC1YsIDExEQmT55MWloanTt3pl+/fmRnZ5fZPiQkhMcee4yUlBTWrVtHQkICCQkJfPXVV642zz//PK+99hqzZs1i1apV+Pn50a9fP06ePOlqM3z4cDZs2MCSJUtYtGgR3377LaNHj672/orUa34NnSGpYRs4uhdm3wiHtptdlYjIOSyGYRhmFhAXF0f37t2ZPn06AA6Hg6ioKMaOHcuECRMqdI6uXbvSv39/pkyZgmEYNG7cmIceeoiHH34YgJycHMLDw5k9ezZDhw5l48aNtG/fnjVr1hAbGwvA4sWLueGGG9izZw+NGzc+5xr5+fnk5+e7vs7NzSUqKoqcnBwCAwMv9dsgUr8czXLeZjuwGYKiYNQX0KC52VWJSD2Qm5tLUFDQBX9/mzqCVFBQQGpqKvHx8a59VquV+Ph4UlJSLni8YRgkJyeTkZHB1VdfDcD27dvJzMwscc6goCDi4uJc50xJSSE4ONgVjgDi4+OxWq2sWrWqzGslJSURFBTk2qKioirVZxEBAsJh5H8gtDXk7Hbebjuyy+yqRERcTA1IBw4coLi4mPDw8BL7w8PDyczMLPe4nJwc/P39sdvt9O/fn2nTptGnTx8A13HnO2dmZiZhYWElnvfw8CAkJKTc606cOJGcnBzXtnv37ovrrIiUFBDhDEkhLSFn16mQpJ8rEakdPMwuoDICAgJIT0/n2LFjJCcnk5iYSMuWLendu3e1XdPLywsvL69qO79IvRTYGEYugtn94fB25223UV9CUBOzKxORes7UEaSGDRtis9nIysoqsT8rK4uIiIhyj7NarbRu3ZqYmBgeeughBg0aRFJSEoDruPOdMyIi4pxJ4EVFRRw6dOi81xWRahDUBEYtguDmcHiHMyTl7jW7KhGp50wNSHa7nW7dupGcnOza53A4SE5OpmfPnhU+j8PhcE2gbtGiBRERESXOmZuby6pVq1zn7NmzJ0eOHCE1NdXV5ptvvsHhcBAXF3ep3RKRixXU9FRIauZ86/+cG+Fo+bfZRUSqm+m32BITExk5ciSxsbH06NGDqVOnkpeXR0JCAgAjRoygSZMmrhGipKQkYmNjadWqFfn5+Xz55ZfMnTuXmTNnAmCxWBg3bhx///vfueyyy2jRogVPPPEEjRs3ZsCAAQC0a9eO66+/nnvuuYdZs2ZRWFjImDFjGDp0aJnvYBORGhDc7MzttoNbnXOSRn3hnNAtIlLDTA9IQ4YMYf/+/UyaNInMzExiYmJYvHixa5L1rl27sFrPDHTl5eVx3333sWfPHnx8fGjbti3z5s1jyJAhrjaPPPIIeXl5jB49miNHjnDVVVexePFivL29XW3ee+89xowZw3XXXYfVamXgwIG89tprNddxETlXg+bOkaR3+sPBLc6RpFGLwD/swseKiFQh09dBclcVXUdBRCrh0K/OEaTc35wrb4/8D/g3MrsqEakD3GIdJBGRMoW0dIaigEjYvxHevQnyDphdlYjUIwpIIlI7hbZyzknyj4DsX+DdmyHvoNlViUg9oYAkIrVXw9bOkSS/MMj6GebeDMcPmV2ViNQDCkgiUrs1utw5UduvEWSud44knThsdlUiUscpIIlI7deojXMkybchZK6DdwfAiSNmVyUidZgCkoi4h7B2MPJz8A2Ffekw9xY4mWN2VSJSRykgiYj7CO8AIz4HnxDYmwbzBsLJXLOrEpE6SAFJRNxLxBUw4jPwaQB71sB7gyD/qNlViUgdo4AkIu4nshPc8Sl4B8HuVTBPIUlEqpYCkoi4p8YxzpEkryDY/SO8Nxjyj5ldlYjUEQpIIuK+GneBEZ+AVyDs+gHeHwIFeWZXJSJ1gAKSiLi3Jt3gjk/AHgA7vz8Vko6bXZWIuDkFJBFxf01j4faPwe4PO76D+cOg8ITZVYmIG1NAEpG6oVkcDP8IPP3g1+Uw/zYoPGl2VSLiphSQRKTuaN4Tbj8VkrZ9AwuGKySJSKUoIIlI3dK8Fwz/ADx9YetS+OAOKMo3uyoRcTMKSCJS90RfBbctAA8f2PI1fDBCIUlELooCkojUTS2uhtvmg4c3bF4MH46CogKzqxIRN6GAJCJ1V8veMPR9sHlBxpfwUQIUF5pdlYi4AQUkEanbWl93KiTZYdMi+OhOhSQRuSAFJBGp+y6LhyHvOUPSxs/h47uhuMjsqkSkFlNAEpH64fK+MHguWD3hl0/hk9EKSSJSLgUkEak/2lwPg+eA1QN+/hg+/TM4is2uSkRqIQUkEalf2vaHP812hqT1H8Kn9ykkicg5FJBEpP5pdyMMehssNlg3Hz4fCw6H2VWJSC2igCQi9VP7m2HQW86QlP4e/EchSUTOUEASkfqrwy0w8F9gscLaebDoQYUkEQEUkESkvrtiINzyT2dISnsXvkhUSBIRBSQRETr9CQbMAiyQ+g58+TAYhtlViYiJPMwuQESkVug8BIxi57vafnoLtiwBux/YPJ0LTHp4nXlss5/1uPQ+r3L2l3rsYT//86XPZ7WBxWL2d0mk3lBAEhE5LeY2MBzOd7Xl7DK7mlIslxi4Tv9ZXtAr9dijIuGtjPMpyEkdoYAkInK2Lrc7P+T2yG4oLnB+bltxARTnn/W4oPzHRRd4vszzldO2BOPUMflmfFcuQjlBrsKB62JG4bwofyTP7lw13eoBNo+zHp/68+zHCnRSBgUkEZHSgpo6NzMZRgVCVmXDW1nnOP04vwLXO+tcjtIf/OsuQe4sFtupsOR5Kkx5lPHY0zk65nrsUX7gqpLzVDDclWhvK3msRvMuiQKSiEhtZLE4R1087GZXcn4XDHKXEt5Kh7PzhbezHp8d3hzFzv2OQnCU89l7RjEUFQMna/RbVyMqFa5sZYe0C4a7SwmG5RzrFwae3qZ860wPSDNmzOCFF14gMzOTzp07M23aNHr06FFm23/961+8++67/PzzzwB069aNZ555pkT7rKwsHn30Ub7++muOHDnC1VdfzbRp07jssstcbXr37s2KFStKnPvee+9l1qxZ1dBDEZE6zF2CHDjDnKP4TFgqPvVnmY/LCFfFReceW+Y5Ck+1Pf248Mx1z3lc3vXLOs95zmmU83E5jlP1F52o2e91VRn+MVwWb8qlTQ1ICxYsIDExkVmzZhEXF8fUqVPp168fGRkZhIWFndN++fLlDBs2jF69euHt7c1zzz1H37592bBhA02aNMEwDAYMGICnpyefffYZgYGBvPzyy8THx/PLL7/g5+fnOtc999zD008/7fra19e3RvosIiImsVicIxM208cGqp5hXHy4K7f9xRx7nvNURTC0eZr2LbUYhnmLfcTFxdG9e3emT58OgMPhICoqirFjxzJhwoQLHl9cXEyDBg2YPn06I0aMYPPmzbRp04aff/6ZDh06uM4ZERHBM888w9133w04R5BiYmKYOnVqhWvNz88nP//MPfXc3FyioqLIyckhMDDwInotIiIiZsnNzSUoKOiCv79NWyiyoKCA1NRU4uPPDJ1ZrVbi4+NJSUmp0DmOHz9OYWEhISEhAK4A4+195n6l1WrFy8uL77//vsSx7733Hg0bNuSKK65g4sSJHD9+/LzXSkpKIigoyLVFRUVVqEYRERFxP6YFpAMHDlBcXEx4eHiJ/eHh4WRmZlboHI8++iiNGzd2hay2bdvSrFkzJk6cyOHDhykoKOC5555jz5497Nu3z3Xcbbfdxrx581i2bBkTJ05k7ty53H777ee91sSJE8nJyXFtu3fvvsgei4iIiLtw2xuxzz77LPPnz2f58uWuESNPT08WLlzIXXfdRUhICDabjfj4eP7whz9w9p3E0aNHux537NiRyMhIrrvuOrZt20arVq3KvJ6XlxdeXl7V2ykRERGpFUwbQWrYsCE2m42srKwS+7OysoiIiDjvsS+++CLPPvssX3/9NZ06dSrxXLdu3UhPT+fIkSPs27ePxYsXc/DgQVq2bFnu+eLi4gDYunVrJXsjIiIidYlpAclut9OtWzeSk5Nd+xwOB8nJyfTs2bPc455//nmmTJnC4sWLiY2NLbddUFAQjRo1YsuWLfz000/cfPPN5bZNT08HIDIy8uI7IiIiInWOqbfYEhMTGTlyJLGxsfTo0YOpU6eSl5dHQkICACNGjKBJkyYkJSUB8NxzzzFp0iTef/99oqOjXXOV/P398ff3B+DDDz+kUaNGNGvWjPXr1/Pggw8yYMAA+vbtC8C2bdt4//33ueGGGwgNDWXdunWMHz+eq6+++pzRKBEREamfTA1IQ4YMYf/+/UyaNInMzExiYmJYvHixa+L2rl27sFrPDHLNnDmTgoICBg0aVOI8kydP5sknnwRg3759JCYmkpWVRWRkJCNGjOCJJ55wtbXb7SxdutQVxqKiohg4cCCPP/549XdYRERE3IKp6yC5s4quoyAiIiK1R61fB0lERESktlJAEhERESlFAUlERESkFAUkERERkVIUkERERERKUUASERERKcVtP4vNbKdXR8jNzTW5EhEREamo07+3L7TKkQJSJR09ehSAqKgokysRERGRi3X06FGCgoLKfV4LRVaSw+Fg7969BAQEYLFYquy8ubm5REVFsXv37jq7AGVd76P65/7qeh/rev+g7vdR/as8wzA4evQojRs3LvFpHaVpBKmSrFYrTZs2rbbzBwYG1sm/9Ger631U/9xfXe9jXe8f1P0+qn+Vc76Ro9M0SVtERESkFAUkERERkVIUkGoZLy8vJk+ejJeXl9mlVJu63kf1z/3V9T7W9f5B3e+j+lf9NElbREREpBSNIImIiIiUooAkIiIiUooCkoiIiEgpCkgiIiIipSggmWDGjBlER0fj7e1NXFwcq1evPm/7Dz/8kLZt2+Lt7U3Hjh358ssva6jSyruYPs6ePRuLxVJi8/b2rsFqL863337LjTfeSOPGjbFYLHz66acXPGb58uV07doVLy8vWrduzezZs6u9zsq62P4tX778nNfPYrGQmZlZMwVfpKSkJLp3705AQABhYWEMGDCAjIyMCx7nLj+Hlemfu/0Mzpw5k06dOrkWEezZsyf//e9/z3uMu7x+cPH9c7fXr7Rnn30Wi8XCuHHjztuupl9DBaQatmDBAhITE5k8eTJpaWl07tyZfv36kZ2dXWb7H374gWHDhnHXXXexdu1aBgwYwIABA/j5559ruPKKu9g+gnO11H379rm2nTt31mDFFycvL4/OnTszY8aMCrXfvn07/fv359prryU9PZ1x48Zx991389VXX1VzpZVzsf07LSMjo8RrGBYWVk0VXpoVK1Zw//338+OPP7JkyRIKCwvp27cveXl55R7jTj+HlekfuNfPYNOmTXn22WdJTU3lp59+4ve//z0333wzGzZsKLO9O71+cPH9A/d6/c62Zs0a3njjDTp16nTedqa8hobUqB49ehj333+/6+vi4mKjcePGRlJSUpntBw8ebPTv37/Evri4OOPee++t1jovxcX28Z133jGCgoJqqLqqBRiffPLJeds88sgjRocOHUrsGzJkiNGvX79qrKxqVKR/y5YtMwDj8OHDNVJTVcvOzjYAY8WKFeW2ccefw9Mq0j93/hk8rUGDBsabb75Z5nPu/Pqddr7+uevrd/ToUeOyyy4zlixZYlxzzTXGgw8+WG5bM15DjSDVoIKCAlJTU4mPj3fts1qtxMfHk5KSUuYxKSkpJdoD9OvXr9z2ZqtMHwGOHTtG8+bNiYqKuuD/lNyNu72GlRUTE0NkZCR9+vRh5cqVZpdTYTk5OQCEhISU28adX8OK9A/c92ewuLiY+fPnk5eXR8+ePcts486vX0X6B+75+t1///3079//nNemLGa8hgpINejAgQMUFxcTHh5eYn94eHi58zUyMzMvqr3ZKtPHNm3a8Pbbb/PZZ58xb948HA4HvXr1Ys+ePTVRcrUr7zXMzc3lxIkTJlVVdSIjI5k1axYff/wxH3/8MVFRUfTu3Zu0tDSzS7sgh8PBuHHjuPLKK7niiivKbeduP4enVbR/7vgzuH79evz9/fHy8uLPf/4zn3zyCe3bty+zrTu+fhfTP3d8/ebPn09aWhpJSUkVam/Ga+hRbWcWqaCePXuW+J9Rr169aNeuHW+88QZTpkwxsTKpiDZt2tCmTRvX17169WLbtm288sorzJ0718TKLuz+++/n559/5vvvvze7lGpR0f65489gmzZtSE9PJycnh48++oiRI0eyYsWKckOEu7mY/rnb67d7924efPBBlixZUqsnkysg1aCGDRtis9nIysoqsT8rK4uIiIgyj4mIiLio9marTB9L8/T0pEuXLmzdurU6Sqxx5b2GgYGB+Pj4mFRV9erRo0etDx1jxoxh0aJFfPvttzRt2vS8bd3t5xAurn+lucPPoN1up3Xr1gB069aNNWvW8Oqrr/LGG2+c09YdX7+L6V9ptf31S01NJTs7m65du7r2FRcX8+233zJ9+nTy8/Ox2WwljjHjNdQtthpkt9vp1q0bycnJrn0Oh4Pk5ORy7y337NmzRHuAJUuWnPdetJkq08fSiouLWb9+PZGRkdVVZo1yt9ewKqSnp9fa188wDMaMGcMnn3zCN998Q4sWLS54jDu9hpXpX2nu+DPocDjIz88v8zl3ev3Kc77+lVbbX7/rrruO9evXk56e7tpiY2MZPnw46enp54QjMOk1rLbp31Km+fPnG15eXsbs2bONX375xRg9erQRHBxsZGZmGoZhGHfccYcxYcIEV/uVK1caHh4exosvvmhs3LjRmDx5suHp6WmsX7/erC5c0MX28amnnjK++uorY9u2bUZqaqoxdOhQw9vb29iwYYNZXTivo0ePGmvXrjXWrl1rAMbLL79srF271ti5c6dhGIYxYcIE44477nC1//XXXw1fX1/jr3/9q7Fx40ZjxowZhs1mMxYvXmxWF87rYvv3yiuvGJ9++qmxZcsWY/369caDDz5oWK1WY+nSpWZ14bz+8pe/GEFBQcby5cuNffv2ubbjx4+72rjzz2Fl+uduP4MTJkwwVqxYYWzfvt1Yt26dMWHCBMNisRhff/21YRju/foZxsX3z91ev7KUfhdbbXgNFZBMMG3aNKNZs2aG3W43evToYfz444+u56655hpj5MiRJdp/8MEHxuWXX27Y7XajQ4cOxhdffFHDFV+8i+njuHHjXG3Dw8ONG264wUhLSzOh6oo5/bb20tvpPo0cOdK45pprzjkmJibGsNvtRsuWLY133nmnxuuuqIvt33PPPWe0atXK8Pb2NkJCQozevXsb33zzjTnFV0BZfQNKvCbu/HNYmf6528/gnXfeaTRv3tyw2+1Go0aNjOuuu84VHgzDvV8/w7j4/rnb61eW0gGpNryGFsMwjOobnxIRERFxP5qDJCIiIlKKApKIiIhIKQpIIiIiIqUoIImIiIiUooAkIiIiUooCkoiIiEgpCkgiIiIipSggiYiIiJSigCQiUgWWL1+OxWLhyJEjZpciIlVAAUlERESkFAUkERERkVIUkESkTnA4HCQlJdGiRQt8fHzo3LkzH330EXDm9tcXX3xBp06d8Pb25ne/+x0///xziXN8/PHHdOjQAS8vL6Kjo3nppZdKPJ+fn8+jjz5KVFQUXl5etG7dmrfeeqtEm9TUVGJjY/H19aVXr15kZGRUb8dFpFooIIlInZCUlMS7777LrFmz2LBhA+PHj+f2229nxYoVrjZ//etfeemll1izZg2NGjXixhtvpLCwEHAGm8GDBzN06FDWr1/Pk08+yRNPPMHs2bNdx48YMYJ///vfvPbaa2zcuJE33ngDf3//EnU89thjvPTSS/z00094eHhw55131kj/RaRqWQzDMMwuQkTkUuTn5xMSEsLSpUvp2bOna//dd9/N8ePHGT16NNdeey3z589nyJAhABw6dIimTZsye/ZsBg8ezPDhw9m/fz9ff/216/hHHnmEL774gg0bNrB582batGnDkiVLiI+PP6eG5cuXc+2117J06VKuu+46AL788kv69+/PiRMn8Pb2rubvgohUJY0giYjb27p1K8ePH6dPnz74+/u7tnfffZdt27a52p0dnkJCQmjTpg0bN24EYOPGjVx55ZUlznvllVeyZcsWiouLSU9Px2azcc0115y3lk6dOrkeR0ZGApCdnX3JfRSRmuVhdgEiIpfq2LFjAHzxxRc0adKkxHNeXl4lQlJl+fj4VKidp6en67HFYgGc86NExL1oBElE3F779u3x8vJi165dtG7dusQWFRXlavfjjz+6Hh8+fJjNmzfTrl07ANq1a8fKlStLnHflypVcfvnl2Gw2OnbsiMPhKDGnSUTqLo0giYjbCwgI4OGHH2b8+PE4HA6uuuoqcnJyWLlyJYGBgTRv3hyAp59+mtDQUMLDw3nsscdo2LAhAwYMAOChhx6ie/fuTJkyhSFDhpCSksL06dN5/fXXAYiOjmbkyJHceeedvPbaa3Tu3JmdO3eSnZ3N4MGDzeq6iFQTBSQRqROmTJlCo0aNSEpK4tdffyU4OJiuXbvyt7/9zXWL69lnn+XBBx9ky5YtxMTE8J///Ae73Q5A165d+eCDD5g0aRJTpkwhMjKSp59+mlGjRrmuMXPmTP72t79x3333cfDgQZo1a8bf/vY3M7orItVM72ITkTrv9DvMDh8+THBwsNnliIgb0BwkERERkVIUkERERERK0S02ERERkVI0giQiIiJSigKSiIiISCkKSCIiIiKlKCCJiIiIlKKAJCIiIlKKApKIiIhIKQpIIiIiIqUoIImIiIiU8v/uXo0ZnwO8gAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lr: float = 4e-2\n",
    "n_epoch: int = 3\n",
    "n_splits: int = 3\n",
    "batch_size: int = 512\n",
    "verbose: bool = True\n",
    "\n",
    "dataset = pd.read_csv(\"./revlog_history.tsv\", sep='\\t', index_col=None, dtype={'r_history': str ,'t_history': str} )\n",
    "dataset = dataset[(dataset['i'] > 1) & (dataset['delta_t'] > 0) & (dataset['t_history'].str.count(',0') == 0)]\n",
    "if dataset.empty:\n",
    "    raise ValueError('Training data is inadequate.')\n",
    "dataset['tensor'] = dataset.progress_apply(lambda x: lineToTensor(list(zip([x['t_history']], [x['r_history']]))[0]), axis=1)\n",
    "dataset['group'] = dataset['r_history'] + dataset['t_history']\n",
    "print(\"Tensorized!\")\n",
    "\n",
    "n_pre_train_groups = len(dataset[dataset['i'] == 2]['group'].unique())\n",
    "if n_pre_train_groups < n_splits:\n",
    "    print(\"Not enough groups for pre-training. Splitting into {} folds.\".format(n_pre_train_groups))\n",
    "    n_splits = n_pre_train_groups\n",
    "\n",
    "w = []\n",
    "plots = []\n",
    "if n_splits > 1:\n",
    "    sgkf = StratifiedGroupKFold(n_splits=n_splits)\n",
    "    for train_index, test_index in sgkf.split(dataset, dataset['i'], dataset['group']):\n",
    "        print(\"TRAIN:\", len(train_index), \"TEST:\",  len(test_index))\n",
    "        train_set = dataset.iloc[train_index].copy()\n",
    "        test_set = dataset.iloc[test_index].copy()\n",
    "        trainer = Trainer(train_set, test_set, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "        w.append(trainer.train(verbose=verbose))\n",
    "        plots.append(trainer.plot())\n",
    "else:\n",
    "    trainer = Trainer(dataset, dataset, init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)\n",
    "    w.append(trainer.train(verbose=verbose))\n",
    "    plots.append(trainer.plot())\n",
    "\n",
    "w = np.array(w)\n",
    "avg_w = np.round(np.mean(w, axis=0), 4)\n",
    "w = avg_w.tolist()\n",
    "print(\"\\nTraining finished!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1.4879, 2.0816, 4.8613, -1.9573, -1.7648, 0.05, 1.4295, -0.1809, 0.8465, 2.0218, -0.2476, 0.3695, 0.5157]\n",
      "1:again, 2:hard, 3:good, 4:easy\n",
      "\n",
      "first rating: 1\n",
      "rating history: 1,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,1d,2d,4d,7d,13d,22d,1.2m,2.0m,3.3m,5.3m\n",
      "difficulty history: 0,8.8,8.6,8.4,8.2,8.0,7.9,7.7,7.6,7.5,7.3\n",
      "\n",
      "first rating: 2\n",
      "rating history: 2,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,4d,9d,18d,1.2m,2.2m,4.0m,7.0m,11.6m,1.5y,2.4y\n",
      "difficulty history: 0,6.8,6.7,6.6,6.5,6.5,6.4,6.3,6.2,6.2,6.1\n",
      "\n",
      "first rating: 3\n",
      "rating history: 3,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,6d,16d,1.3m,2.7m,5.5m,10.5m,1.6y,2.7y,4.4y,7.0y\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9,4.9\n",
      "\n",
      "first rating: 4\n",
      "rating history: 4,3,3,3,3,3,3,3,3,3,3\n",
      "interval history: 0d,8d,24d,2.1m,5.0m,10.7m,1.8y,3.3y,5.8y,9.8y,15.8y\n",
      "difficulty history: 0,2.9,3.0,3.1,3.2,3.3,3.3,3.4,3.5,3.6,3.6\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(w)\n",
    "\n",
    "class Collection:\n",
    "    def __init__(self, w: List[float]) -> None:\n",
    "        self.model = FSRS(w)\n",
    "        self.model.eval()\n",
    "\n",
    "    def predict(self, t_history: str, r_history: str):\n",
    "        with torch.no_grad():\n",
    "            line_tensor = lineToTensor(list(zip([t_history], [r_history]))[0]).unsqueeze(1)\n",
    "            output_t = self.model(line_tensor)\n",
    "            return output_t[-1][0]\n",
    "\n",
    "    def batch_predict(self, dataset):\n",
    "        fast_dataset = RevlogDataset(dataset)\n",
    "        with torch.no_grad():\n",
    "            outputs, _ = self.model(fast_dataset.x_train.transpose(0, 1))\n",
    "            stabilities, difficulties = outputs[fast_dataset.seq_len-1, torch.arange(len(fast_dataset))].transpose(0, 1)\n",
    "            return stabilities.tolist(), difficulties.tolist()\n",
    "        \n",
    "requestRetention = 0.9\n",
    "\n",
    "my_collection = Collection(w)\n",
    "preview_text = \"1:again, 2:hard, 3:good, 4:easy\\n\"\n",
    "for first_rating in (1,2,3,4):\n",
    "    preview_text += f'\\nfirst rating: {first_rating}\\n'\n",
    "    t_history = \"0\"\n",
    "    d_history = \"0\"\n",
    "    r_history = f\"{first_rating}\"  # the first rating of the new card\n",
    "    # print(\"stability, difficulty, lapses\")\n",
    "    for i in range(10):\n",
    "        states = my_collection.predict(t_history, r_history)\n",
    "        # print('{0:9.2f} {1:11.2f} {2:7.0f}'.format(\n",
    "            # *list(map(lambda x: round(float(x), 4), states))))\n",
    "        next_t = max(1, round(float(9 * states[0] * (1/requestRetention - 1))))\n",
    "        difficulty = round(float(states[1]), 1)\n",
    "        t_history += f',{int(next_t)}'\n",
    "        d_history += f',{difficulty}'\n",
    "        r_history += f\",3\"\n",
    "    preview_text += f\"rating history: {r_history}\\n\"\n",
    "    preview_text += \"interval history: \" + \",\".join([f\"{ivl}d\" if ivl < 30 else f\"{ivl / 30:.1f}m\" if ivl < 365 else f\"{ivl / 365:.1f}y\" for ivl in map(int, t_history.split(','))]) + \"\\n\"\n",
    "    preview_text += f\"difficulty history: {d_history}\\n\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([5.6511, 4.8613])\n",
      "tensor([15.5477,  4.8613])\n",
      "tensor([37.5674,  4.8613])\n",
      "tensor([82.1979,  4.8613])\n",
      "tensor([165.8580,   4.8613])\n",
      "tensor([8.3540, 8.2144])\n",
      "tensor([ 2.6322, 10.0000])\n",
      "tensor([3.7900, 9.7431])\n",
      "tensor([5.5249, 9.4990])\n",
      "tensor([8.3259, 9.2671])\n",
      "tensor([12.2644,  9.0468])\n",
      "tensor([18.3561,  8.8375])\n",
      "rating history: 3,3,3,3,3,1,1,3,3,3,3,3\n",
      "interval history: 0,6,16,38,82,166,8,3,4,6,8,12,18\n",
      "difficulty history: 0,4.9,4.9,4.9,4.9,4.9,8.2,10.0,9.7,9.5,9.3,9.0,8.8\n"
     ]
    }
   ],
   "source": [
    "test_rating_sequence = \"3,3,3,3,3,1,1,3,3,3,3,3\"\n",
    "requestRetention = 0.9  # recommended setting: 0.8 ~ 0.9\n",
    "easyBonus = 1.3\n",
    "hardInterval = 1.2\n",
    "\n",
    "t_history = \"0\"\n",
    "d_history = \"0\"\n",
    "for i in range(len(test_rating_sequence.split(','))):\n",
    "    rating = test_rating_sequence[2*i]\n",
    "    last_t = int(t_history.split(',')[-1])\n",
    "    r_history = test_rating_sequence[:2*i+1]\n",
    "    states = my_collection.predict(t_history, r_history)\n",
    "    print(states)\n",
    "    next_t = max(1, round(float(9 * states[0] * (1/requestRetention - 1))))\n",
    "    if rating == '4':\n",
    "        next_t = round(next_t * easyBonus)\n",
    "    elif rating == '2':\n",
    "        next_t = round(last_t * hardInterval)\n",
    "    t_history += f',{int(next_t)}'\n",
    "    difficulty = round(float(states[1]), 1)\n",
    "    d_history += f',{difficulty}'\n",
    "preview_text = f\"rating history: {test_rating_sequence}\\n\"\n",
    "preview_text += f\"interval history: {t_history}\\n\"\n",
    "preview_text += f\"difficulty history: {d_history}\"\n",
    "print(preview_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loss before: 0.3251, loss after: 0.3084, improvement: 0.0167\n"
     ]
    }
   ],
   "source": [
    "my_collection = Collection(init_w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = power_forgetting_curve(dataset['delta_t'], dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_before = dataset['log_loss'].mean()\n",
    "\n",
    "my_collection = Collection(w)\n",
    "stabilities, difficulties = my_collection.batch_predict(dataset)\n",
    "dataset['stability'] = stabilities\n",
    "dataset['difficulty'] = difficulties\n",
    "dataset['p'] = power_forgetting_curve(dataset['delta_t'], dataset['stability'])\n",
    "dataset['log_loss'] = dataset.apply(lambda row: - np.log(row['p']) if row['y'] == 1 else - np.log(1 - row['p']), axis=1)\n",
    "loss_after = dataset['log_loss'].mean()\n",
    "\n",
    "tmp = dataset.copy()\n",
    "tmp['stability'] = tmp['stability'].map(lambda x: round(x, 2))\n",
    "tmp['difficulty'] = tmp['difficulty'].map(lambda x: round(x, 2))\n",
    "tmp['p'] = tmp['p'].map(lambda x: round(x, 2))\n",
    "tmp['log_loss'] = tmp['log_loss'].map(lambda x: round(x, 2))\n",
    "tmp.rename(columns={\"r\": \"grade\", \"p\": \"retrievability\"}, inplace=True)\n",
    "tmp[['id', 'cid', 'review_date', 'r_history', 't_history', 'delta_t', 'grade', 'stability', 'difficulty', 'retrievability', 'log_loss']].to_csv(\"./evaluation.tsv\", sep='\\t', index=False)\n",
    "del tmp\n",
    "print(f\"loss before: {loss_before:.4f}, loss after: {loss_after:.4f}, improvement: {loss_before - loss_after:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R-squared: 0.9571\n",
      "RMSE: 0.0147\n",
      "[0.04643835 0.95018134]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Last rating: 1\n",
      "R-squared: 0.4999\n",
      "RMSE: 0.0393\n",
      "[0.2442089  0.70882616]\n",
      "\n",
      "Last rating: 2\n",
      "R-squared: -0.5135\n",
      "RMSE: 0.0918\n",
      "[-0.55497845  1.50964349]\n",
      "\n",
      "Last rating: 3\n",
      "R-squared: 0.9344\n",
      "RMSE: 0.0200\n",
      "[-0.00319453  1.01767817]\n",
      "\n",
      "Last rating: 4\n",
      "R-squared: -0.2076\n",
      "RMSE: 0.0398\n",
      "[0.46238926 0.53126459]\n"
     ]
    },
    {
     "data": {
      "image/png": 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qFefPn+e3336jcePGecrwKCoK8jXQIiv2Y53adsD22/nz57l9+zabN2/GYDDYu4MUJSZT/u9tucHf3x9vb+8iXYeghBJxxprteuIXkFTQ+T0Yshq8A3OcVSAQCEoCJSUmFWROaY5JcyI/MamSKvc1P70mRUwqcAjGRPhrLKwaBaYECGmfXG/g0UJbRcOGDfH19bX/zZkzJ1/LiYyMRKfT8eGHH9KzZ0/++ecfBgwYwBNPPMHOnTsBuHPnDi4uLhk+bgUGBnLnzh37NKmFV9t42zhHIMTXMozBLKf5YlcQz1dTum4X8QWwMCgOjMkFt1w0Kqoni6+pBWRFUUgwJhT7X24Fynr16lGpUiVCQ0Ptv4WGhtKvXz9q1KhhT7e3/d65c2fA+iVpzpw51KhRA3d3d5o2bcoff/yRZtr0Xby+++47qlatioeHBwMGDGDu3LmZfsVftmwZISEh+Pr68swzzxAfH4+swPuvv8Lh/Xv4efFC+xfmq1evAnDq1Cl69eqFl5cXgYGBDBkyhHv37tmXmZCQwNChQ/Hy8qJSpUp89tlnudo/2RETE8PIkSMJCAjAx8eHLl26cOLECfv4y5cv069fPwIDA/Hy8qJVq1Zs3bo1zTIWLFhAnTp1cHNzIzAwkCeffBKA4cOHs3PnTr744osM25qa06dPc/nyZRYsWECbNm2oXr06Dz/8MLNmzaJNmzb26Q4ePEjz5s1xc3PjwQcfZPXq1UiSxPHjx4HMMyrWrFmT5kUlN9sTEhLCzJkzGTp0KD4+Prz00ksA/Pvvv7Rv3x53d3eqVq3Kq6++SkJCgn2+b775JsN+sGW9alQqe8EtWVHsFhQVK1YkKCiIFi1aMH78eK5fv54msyKndd6+fZs+ffrg7u5OjRo1+OWXXwgJCeHzzz+3TyNJEt988w2PP/44np6ezJ49G4C//vqLFi1a4ObmRs2aNZk+fbo9U0dRFKZNm0a1atVwdXUlODiYV199NcdjDhkzS6Kjoxk6dCjlypXDw8ODXr16cfHiRft423HbvHkzDRo0wMvLi549e3L79m0EpQRFgSM/wned4d4F8K4Ew/6GjhNBpXZ06wQCQQnBUfFoaYxJIWOcplar7QVcRExa+mLSnMhPTJqYJia9JWJSgfMTeQ6+6wLHlmGtN/BOkdQbOHPmDLGxsfa/SZMm5Ws5crJdXb9+/Xj99ddp1qwZ77zzDo899hgLFy4szCYXO8JorAyTZEzryxqnN6MoSr6+MJc02wFDsvjqqlFRrbwHmIwYzCn7I9GUiNccr2Jvl26SDk8Xz1xN27lzZ3bs2ME777wDWLMJ3nrrLSwWCzt27KBTp04kJSVx4MABXnzxRQDmzJnDzz//zMKFC6lTpw67du1i8ODBBAQE0LFjxwzr2LNnDy+//DIfffQRjz/+OFu3buX999/PMN3ly5dZs2YN69atIzo6mqeffpoPP/yQwWPf5q3pc7gWdona9Rry5SdzUKkkypcvz61bt+jatSsjR45k3rx5JCUl8fbbb/P000+zfft2ACZOnMjOnTv566+/qFixIu+++y5Hjx4tkJ/XU089hbu7Oxs3bsTX15dFixbx6KOPcuHCBfz9/dHpdPTu3ZvZs2fj6urKTz/9RN++fTl//jzVqlXj8OHDvPrqqyxbtox27doRFRXF7t27Afjiiy+4cOECDzzwADNmzAAgICAgQxsCAgJQqVT88ccfjB8/HrU6oxij0+l47LHH6NatGz///DNhYWG89tpred7enLbHxqeffsqUKVOYOnUqYD2mPXv2ZNasWfzwww/cvXuXsWPHMnbsWBYvXsyxY8d47bXXMuwHm9+rRi2hkkAlScnia9p7RGxsLL/++itgzW7JaZ1LliwBYOjQody7d4/Q0FC0Wi0TJkwgMjIyw3ZPmzaNDz/8kM8//xyNRsPu3bsZOnQoX375Je3bt+fy5cv2gH7q1Kn8+eefzJs3j19//ZVGjRpx584d+wtQdsc8M4YPH87FixdZu3YtPj4+vP322/Tu3ZszZ86g1VqrhyYmJvLpp5+ybNkyVCoVgwcP5s0332T58uV5PsYCJ8MQby1icHKldbh2VxiwCDwrOLZdAoGgxOGoeBRKX0w6e/bsDHGaLMu4uroSExNDly5dRExaymLS3JKXmPR6xESmf/Y1AG+N+x/6+BgRkwqcl2PLYcObVtsrr0B44juomfH+Whh4e3vj4+NT4OVUqFABjUZDw4YN0/zeoEED/v33XwCCgoIwGo3ExMSk+egTERFBUFCQfZqDBw+mWUZERIR9nENQyhjXr19XACUsLMzRTXE416MSlOpvr1NqvLNOqf629S8uyZivZe26EGlfRvW31ykbT94u5NamYDQalTVr1ihGY/7aqiiKMnDBnuR23lIOX7qj/LPniHLq2l37eJ1BpzCNYv/TGXS53obvvvtO8fT0VEwmkxIXF6doNBolMjJS+eWXX5QOHTooiqIo27ZtUwDl2rVril6vVzw8PJS9e/emWc6IESOUZ599VlEURdmxY4cCKNHR0YqiKMqgQYOUPn36pJn++eefV3x9fe3DU6dOVTw8PJS4uDj7bxMnTlRat26tnLoZo5y4Hq082OZh5fkRLytGs0VRFEWxWCzK5MmTlW7duqVZtu36PH/+vBIfH6+4uLgov//+u338/fv3FXd3d+W1117Lcr8sWbIkTftSs3v3bsXHx0fR6/Vpfq9Vq5ayaNGiLJfZqFEj5auvvlIURVH+/PNPxcfHJ832pqZjx47Zts/G119/rXh4eCje3t5K586dlRkzZiiXL1+2j1+0aJFSvnx5JSkpyf7bN998owDKsWPHstzW1atXKznd2lNvj6IoSvXq1ZX+/funmWbEiBHKSy+9lOa33bt3KyqVSklISFB++umnTPfDfZ1BOXE9Wrly13oun70Vq5y4Hq1s3LxVARRPT0/F09NTwVqzQHn88cdztc6kpCTl7NmzCqAcOnTIPv7ixYsKoMybN8/+G6CMHz8+zXIeffRR5YMPPkjz27Jly5RKlSopiqIon332mVK3bt1M7yt5OeYXLlxQAGXPnj328ffu3VPc3d3t5/KSJUsUQLl06ZJ9mvnz5yuBgYGZLl9RFCUpKUk5c+ZMmvOhIBTGfVSQCbdOKMqXLRRlqo+iTCunKLvnKorFUiSrCgsLUwDl+vXrRbJ8QdEjYtKSTWHfRzO7zzsqHi2NMamN1M9si8WiREdHKzNmzFC6d++eZtkiJi35MWlW2M6t/MakBy/eVtbsOKAAyoGDB+3jRUyaP0RMWgTo4xVl1f+s8ehUH0X58XFFiY8oklUVNB4FlNWrV6f5rW3btsrgwYPT/Na/f3/78yEmJkbRarXKH3/8YR9/7tw5BVD27dunKIqibNiwQVGpVEpERMp2L1q0KNP7bnEhMl/LMDa/Vx93LYkGC0aLTJzejLebNs/Lypj56uS2A5YU24Fq5T2IirBWZLfIMmqVCg+tB7pJumJvl4fWI9fTdurUiYSEBA4dOkR0dDR169a1Zwu88MIL6PV6QkNDqVmzJtWqVeP06dMkJibSrVu3NMsxGo00b94803WcP38+QxXChx56iHXr1qX5LSQkJI2/UKVKlYiMjCS9FZJFVki2AeXUqVOEhobi5ZUxo+Py5cskJSVhNBpp3bq1/Xd/f3/q1auX477JihMnTqDT6Shfvnya35OSkuzFH3Q6HdOmTWP9+vXcvn0bs9lMUlKSvVtat27dqF69OjVr1qRnz5707NmTAQMG4OGR+2MHMGbMGIYOHUpoaCj79+9n5cqVfPDBB6xdu5Zu3bpx9uxZmjRpgpubm32etm3b5nmbc9oeGw8++GCa4RMnTvDff/+l+eqtKAqyLBMWFkanTp0y3Q9mi9VqQKuyZtCrVRJYwJLcfXH37t14eHiwf/9+PvjggzTdR3Ja54ULF9BoNLRo0cI+vnbt2pQrVy7Ddme2PXv27LF39wKwWCzo9XoSExN56qmn+Pzzz+3b07t3b/r27YtGo8nTMT979iwajSbNeVu+fHnq1avH2bNn7b95eHik8byzXTMC50CW5Tx53fn5+qI6ugQ2vQsWA/hUhid/gGptcp5ZIBAIssBR8aht3bmlJMSk2XHixAl27NghYtJSFpPmtB/yG5PevH6Na1cuo9FoaNos5XwVManAKYg4DSuHI989T4xegvYToM0YMKogKirL2fz8/FCpiseVVKfTcenSJftwWFgYx48fx9/fn2rVqjFx4kQGDRpEhw4d6Ny5M5s2beLvv/+229v4+voyYsQIJkyYgL+/Pz4+PowbN462bdva7VK6d+9Ow4YNGTJkCB9//DF37tzhvffeY8yYMbi6uhbLdqZHiK9lGJv46umiQaNScU9nIDbRRGU/9zwvK6Pnq3PbDtg9X9VqvN20VoEIqx2Bh4sKSZJy3dXKUdSuXZsqVaqwY8cOoqOj7V20goODqVq1Knv37mXHjh106dIFsN7kANavX0/lypXTLKugNyBbtxUbkiQhy3IGvzA51bCtC9PHH3+cYXmVKlVKc0MuLHQ6XQZfMhu2LgtvvvkmW7Zs4dNPP6V27dq4u7vz5JNP2g34vb29OXr0KKGhofzzzz9MmTKFadOmcejQoTxXtPX29qZv37707duXWbNm0aNHD2bNmpXhZSQrVCpVhn2c3sg/p+2x4emZ9nzX6XT873//S+MxZaNKlSro9XoOHz7Mrl270uyHv7bsAo07mmS/V41aBSaL3V+6Ro0a+Pn5Ua9ePSIjIxk0aBC7du3KcZ3VqlXjwoULudovWW3P9OnTeeKJJzJM6+bmRtWqVTl//jxbt25ly5YtvPLKK3zyySfs3LmzUI+5jcyumfTHUuA4YmJimLvuGG6eORet0MfeYwI/4R++0fpD3Z7Q/xvw8C/iVgoEgtJOSYhHoWTEpNmh0+no27cvH330UYZxIiYtuTFpTvshPzHphTvxBAZX5toVq0Butii45pC3JGJSQbGgKHD0J9j4Fpj1xGgCmVt1Cm6GerDzSraz6hPimfBYc/z9iyd2PXz4sN3/G2DChAkADBs2jKVLlzJgwAAWLlzInDlzePXVV6lXrx5//vknjzzyiH2eefPmoVKpGDhwIAaDgR49erBgwQL7eLVazbp16xg9ejRt27bF09OTYcOG2W1YHIEQX8swiQarQOrhosZNmyy+5rPoVvrMV52hZIivrtpkgShZfNWbZDxcHNasPNO5c2dCQ0OJjo5m4sSJ9t87dOjAxo0bOXjwIKNHjwasFQhdXV0JDw/P1EsrM+rVq8ehQ4fS/JZ+ODe4uLhgsVjSFHhr2rQp69evJyQkBI0m462oVq1aaLVaDhw4YPeBio6O5sKFC7luf3patGjBnTt30Gg0hISEZDrNnj17GD58uD27QqfTZShQoNFo6Nq1K127dmXq1Kn4+fmxfft2nnjiCfu25hVJkqhfvz579+4FrL42y5YtQ6/X2zMNUhetAKtPV3x8PAkJCfbAzlb4IC/bkxktWrTgzJkz1K5dO8M4WZbR6/WZ7oddoTto17U3WrX1mrJdW5ZMgrgxY8YwZ84cVq9ezYABA7JdJ1jPR7PZzLFjx2jZsiUAly5dIjo6Olfbc/78+SyXDeDu7m5/8RgzZgz169fn5MmTtGjRIttjnpoGDRpgNps5cOAA7dq1A+D+/fucP38+g3eRwLlx8/TG08cv+4nib8OldWDZAJ5a6Dod2o6BXHqny7JC2P0E/rsRw4nrsZy4EUO3hoG80inr81QgEAickZIWk6amRYsWrFq1SsSkyZSWmDSzOC0rchuTJrnHoigKNWrXwWw2c/ToUdq3s2aWiphU4DAM8fD3eDiVXLSwdlfo+CFuB6NzjmWz4G68gXIeWntCTWHSqVOnHAX+F1980e4Rnhlubm7Mnz+f+fPnZzlN9erV2bBhQ77bWdgI8bUMk5Cc+erhqiFZHyk08dXZbQcM9szX5C7Salvma94DFEfSuXNnxowZg8lkShP8dezYkbFjx2I0Gu1flby9vXnzzTd5/fXXkWWZRx55hNjYWPbs2YOPjw/Dhg3LsPxx48bRoUMH5s6dS9++fdm+fTsbN27MU1E2SZKoWq06J48dISwsjOAAf/z8/Bg5ciTLli3j2Wef5a233sLf359Lly7x66+/8v333+Pl5cWIESOYOHEi5cuXp2LFikyePDlX3SEsFkuGgM/V1ZWuXbvStm1b+vfvz8cff0zdunW5desW69evZ8CAATz44IPUqVOHVatW0bdvXyRJ4v3330+TMbFu3TquXLlChw4dKFeuHBs2bECWZXvXs5CQEA4cOMDVq1fx8vLC398/Q5uPHz/O1KlTGTJkCA0bNsTFxYWdO3fyww8/8PbbbwPw3HPPMXnyZEaNGsWkSZO4evUqn376aZrltG7dGg8PD959911effVVDhw4wNKlS9NMk9P2ZMXbb79NmzZtGDt2LCNHjsTT05MzZ86wZcsWvvzySzZt2kRERAQdO3ZMsx+q16wDgNae+Zosvqb3oMDazWnUqFFMnTqV/v37Z7vOr7/+mvr169O1a1deeuklvvnmG7RaLW+88Qbu7u45npNTpkzhscceo1q1ajz55JOoVCpOnDjBqVOnmDVrFkuXLsVisdj36c8//4y7uzvVq1fP8Zin39/9+vVj1KhRLFq0CG9vb9555x0qV65Mv379ctzvgpKCAjeOwOXtoE8C/8owfBlUeTDrORSF27F6q9B6I5b/bsTw343YDD1F/Ny10KmImy8QCASFTEmISSFtnObh4YFGo+GVV17h+++/FzFpKYtJ82ILkduY9NfV65g06xPq1atPm/adGDdmNN8uWihiUoHjuH0CVg6HqCsgqeHRKdDuVYiJAXL+GJAZZovMyB+tH7e+eKY5IRWcvwdGSaB4TB0ETkmiMTnzVavG193a3SAun6KpyVyybAfs4qsmVddowGDKOQBwJjp37kxSUhK1a9cmMDDQ/nvHjh2Jj4+nXr16VKpUyf77zJkzef/995kzZw4NGjSgZ8+erF+/nho1amS6/IcffpiFCxcyd+5cmjZtyqZNm3j99dfTeD5lhe2MUEnw0tjXUKvVtGnZjICAAMLDw6lUqRK7d+/GYrHQvXt3GjduzPjx49P4zXzyySe0b9+evn370rVrVx555BF7xmN26HQ6mjdvnubPFuht2LCBDh068MILL1C3bl2eeeYZrl27Zt9/c+fOpVy5crRr146+ffvSo0ePNB6jfn5+rFq1ii5dutCgQQMWLlzIihUraNSoEWDtUqVWq2nYsKF9W9NTpUoVQkJCmD59Oq1bt6ZFixZ88cUXTJ8+ncmTJwPg5eXF33//zcmTJ2nevDmTJ0/O0B3O39+fn3/+mQ0bNtC4cWNWrFjBtGnT0kyT0/ZkRZMmTdi5cycXLlygffv2NG/enClTphAcHAxYvXZWr16dYT+E1LEGf5p0ma9yJuIrwNixYzl79iwrV67McZ0AP/30E4GBgXTo0IEBAwYwatQovL29czwne/Towbp16/jnn39o1aoVbdq0Yd68eVSvXh2wHtfvvvuOhx9+mCZNmrB161b+/vtvypcvn+MxT8+SJUto2bIljz32GG3btkVRFDZs2JChW5eghGJOglOr4dJWUGTwrwUvrM9SeFUUhblbLvDQB9to9+F2Xv75KN+EXmbPpfvE6824alS0qObH8HYhzBvUlKl9Mz+vBAKBwJlx5pg0NanjtMDAQG7cuEFwcDB79uwRMWkpi0mzitOyIjcxaUCgtUq6Ri0xa943VKhYUcSkAsegKHDwO/i+m1V49akCL2yER8ZDAb1bF+26wokbsVy5l2DvKSwoOJJSxgw9bty4QdWqVQkLC8uyi0dZYcXBcCatOknXBhXxdNXw1/FbvNenASPb18zzspYfuMbk1afsw30aV2L+8zk/TPODyWRiw4YN9O7dO98PjibTNhOnN7PtjY5U9tZw7sIlJJ+KuLm5US/Ip5BbXLoYNWoU586dY/fu3dlOl2g0cylSh1atwtNVQ0yikUq+7gR4uyLLMnFxcfj4+BSbsXdp4OrVq9SoUYNjx47RrFkzh7Ujq+OnKAqnbsahoNCgkg9atYqoBCM3ohPxctVQMyBjIYuCYrunb926lUcffbTQl+8s6PV6wsLCqFGjRp5fNDOjMO6jpZmoqCgW7LiUsatW3C048xfoY0FSQa0uJPjU4pXOdTL1yVIUhel/n2Hp3quAtQBd3UBvmlbxpUkVP5pW9aVuoDdatYoTd04weftkxrQaQ686vXJso+1+cP36dapUqVIIWy0obkRMWrIp7PtoYd/nywK5jUmzQsSj+cfZY9IiWZeicOpmLAB+7i7EJBkJ9HEj0Md6vYqYNH+ImDQf6GNh7ThrTApQtxf0X5Cm3kCWsWwmJMTF8Ern2vj7+3PuThx9v/oXk0Xhs6eaMrBl9jGmiEdzj7AdKMMk2D1fNfi4WW90+bYdMKezHXB2z1dLWtsBjVqFBasXrCwrqFR568JUmvn000/p1q0bnp6ebNy4kR9//DGNmXVW2BIdVZJEchJkpr6fgtKDWVZQUJBIyXi1e75mkfmaV7Zv345Op6Nx48bcvn2bt956i5CQEDp06FAoyxcIMkeB64fgSqg129XdDxr2A+9KEBeT+RyKwqz1Z+3C68x+jXiyZVXcXdRpprsUdYkpO6aw4tQKACITIulZu2eeu9IKBAJBaSe/MalAUCikCmU1aokDe3ahsRjo1PZBEZMKio+bR+GPFyD6Kqg00G0GtHkl1/UGssNkkXlz5QlMFoWuDSryRIvKOc8kyDVCfC3DJCZ7vnq6prIdyLfnq/Vp5OmiJsFocWrPV0VR7LYDtjR6tUpCUUkoWC0J0r8cl2UOHjzIxx9/THx8PDVr1uTLL79k5MiROc5n62aukrCL2Vl1PReUDszJHzU0apVdOLLZD5gL6dibTCbeffddrly5gre3N+3atWP58uXiS7mg6DAlwbn1cD+52nVAfajXEzRZZ3soisKHG8+x+N8wAOY80ZhnH6qWZppb8beYsXMGi48txixbP1g+88AzzOg0QwivAoFAkAn5jUkFgsJASaW+atUSZpOJT2dPZcy1qyImFRQ9igIHFsI/74NsAr9q8ORSqJKz/Ulu+Sb0MqduxuHrruWDAY1FPFrICPG1DGMTX921Grv4mt/MV1smaTlPFxKMSU7t+WqWFWwJmK5qNWDdDy5qFQbFWnRLiK8p/P777/maT07eySqVhLqQsx/LKiEhITlWhnQkto8wmlSZ47b/W687pcAP8R49etCjR48CLUMgyDWxN+DMWjDEgUptrR4b3AzI+jxWFIVPNp9n0a4rAMzq/0Aa4TUqKYoP//2Qrw5+hd6sB6BX7V7M7jKb5pWaF+XWCAQCQYkmvzGpoPBx9pi0KFDSZL6qeLjTo/To0aNIbLUEgjQkRcNfY+HcOutw/ceg33xrT6xC4tztOL7cdhGAGf0aUdFH2N8UNkJ8LcPYCm6lznzNr/hqThZdynu6cCM6CZ0Ti6/GVBYJLhoVyFbx1VWtwmBOKcYlKBhpbQeSM1/LWJBW1jAlf4TRqlM8tzTJ/luKoiAriv1cEAicGlmGG4fg7lHr25Z7OWjUH7wCc5x13pYLLAi9DMD0xxsxuI21gIbOqOOL/V/wyd5PiDVYPeMervowcx6dQ/vq7YtsUwQCgUAgEBSc1G8xqZMLBIIi5cZhWPkCxIaD2gW6z4aHRhWKzYANWVF4/6/TmGXo0SiQx5sGY7QYUUtq1CqRlFZYCPG1DJNgsIqOHi4afNytp0JcPkVTU6rMV8CpbQfSi68mY/L/tSowK+hNFge1rHRhz3yVEJmvZQRbAGqzGgBr5rNKkpAVBbNFQS3qWQicnYR7Vi+taz7g7gqBDaFuD1C75jjrF1sv8uV2qz3B+481ZFi7EAxmA98e+ZZZu2cRmRAJQJPAJnzQ5QN61+ktunQJBAKBQFACsOWQSJIkxFdB0SPLsH8+bJ0GshnK1YCnlkBw4feSOnotmgsR8VQo78+s/o1RUBiyeghm2czPA37GXete6OssiwjxtQyTZLIV3FLjU8DMV5v46u9hFV8TjBYssmIX3ZwJW2arJrk7vG2LrcW3LCLztZBI8Xy1im8gxNfSTmaZr2AVY41mBbOskLN8JRA4kKv/wp8jIfIWqPpDvV5QqQnZ2QzY+Hr7ReZtvQDA5N4NGN6uGj+d+ImpoVO5GnMVgFrlajGj8wyeeeAZVJL4EiEQCAQCQcnB+h4jAerknl0WS+HYagkEaUiMgtUvw8XN1uFGA6Dvl+DmU+iriozTczQ8BoCZ/R8gwNuVCZsn8Pvp39GqtJyIOEGbKm0Kfb1lESG+lmFSMl8Lbjtg83z1T858BdAZzPblOhO2zFcXTdoXX+uwVXwVD9GCY7cdSOX5KmwHSjc2+xGtOu21o1GpMCKL7ACB8yJbYPdnEDoHFBn8a0HwsxBUK1ez//BvGF/vvQPA2z3rEVDxP5oufJzTd08DUMmrElM6TmFE8xFo1c73XBQIBAKBQJA99sxXUnp5KShYFAWNeG8UFBbX9sGfIyDuprXXVa8PoeULhWozYMMiy2w+cwcF6N4wkMeaBDN331zm7Z8HwNL+S4XwWogI8bUMk+L5qsHHrXA8Xz1dNbhoVBjNMvF6k3OKr5bkAlvpxFetWmXvHm00y7hqhb9JQUhtO6Cy2w44skWCosaW+apJn/lq65olTgCBMxIfAatGQdhO63DT56Dtu7Dndq5mP3Ejmv1XolG7ezOwlZYfLw3mwM4DAJRzK8c7j7zD2IfG4qH1KKotEAgEAoFAUMTYUggkKaWmhUVRsFgUNKIzi6CgyDLsmQfbZ4NigfK14amlENS4yFa5/0oUUQkm3LUq3u3dgN9O/cYb/7wBwMddP+a5xs8V2brLIkJ8LcMkGq0ipLuLGl8Pq0hqNMvoTRbc8ig8pnQ3lvB21XDfbCTeSYtu2WwFXNIJRJIk4apRkWSyZr8K8bVgpIivKQW3LCLztVRjsmW+qjIXX4XthMDpuBIKf46ChEjQekCfz6DZcxAVlavZj4VbhVeA8gH7mHtqNgAeWg/Gtx7PxIcn4ufmV0SNFwgEAoFAUFwoqdVXQK2WsAhbLUFhoLsLq/8Hl7dZhxs/DY/NBVfvIlvlnTg9h69ZY9j2dQI4ff8gQ9cNBWDcQ+N4s92bRbbusor4RlOGsYmvni4avFw02OxZ4/KR/WpM5fXo7WbV9HUG5xZfXbUZT39XjVVw1ZtF0a2CUtXfk+2b1lvF1+Rdbat4X5gsXboUPz8/+/C0adNo1qyZfXj48OH079+/UNeZEyEhIXz++efFuk5HIysKZjnlI0xq1GpRlEDgZMgW2PEB/NTfKrxWbAijdliF11xy4noMuy7eAyBW8ydHdbPRqrSMbTWWy69eZvajs4XwKhAIBE6AJEmsWbOmyNcjYtLSjZLK8xWstlogkgsEBeTqv7DwEavwqnGHx7+GJ74tUuHVLMv8c9pql1Uv0Atvj0QGrxqM0WJkYIOBzOsxT1gwFgFCfC3DJBhSCm6pVBLeBbAesGe8qVX25cTr82dhUNQYs8h8hRRB1mAqOd2j9+3bh1qtpk+fPnmetzgCMpUKe8EtSBug3Llzh3HjxlGzZk1cXV2pWrUqffv2Zdu2bfle35tvvlmg+fNC+iDbxqFDh3jppZeKpQ3Ogs16RJKkDIX2bMGpbRqBwKHE3YYfH4edHwEKtBgKI7dBxfq5XsSBq7cJvXAXAIN0lnjNHwxtOpTzY8/zVe+vCPIKKqLGCwQCgfPi7DFpdoiYVJATds/X5DDXFu+K5AJBvpAtEPoR/NgXdHegQj0YtR1aDCkSf9fU7L98n+hEEx4ualqEuLHy9EriDfE8Uu0Rfn7iZ9Qq0QO4KBC2A2WYJGNKwS0AX3ctsUkm4vIhmtq8HLUaFV6u1tPKWW0HUgpuZbypuCUb9hhKUObr4sWLGTduHIsXL+bWrVsEBwc7uklpUEuSVZBL9kWSZQW1WiI8PJxevXrh5+fHJ598QuPGjTGZTGzevJkxY8Zw7ty5fK3Py8sLLy+vArXZaDTi4uKS84RZEBAQUKD1l0Ts9wCVlOFLqcae+VpyPmoISimXtsKq/0HiPXDxgsc+hyZP5Xr2RFMCa0+dICLKeo3rpTNUrWBg9VP/8nC9h4uo0QKBQFAycPaYNCuuXr1K+/btRUwqyBVScu6rvaaBiG8FeSV9vYFmz0PvT8DFs8hXfTs2iSPhMQC0r+PHH2dXEG/SUTewLn898xduGrcib0NZRWS+llEURSEhVcEtwF4cK3+ZrynCi812wPnF18wyX5NtB4wWEgwmEo3mYv1T8tglX6fT8dtvvzF69Gj69OnD0qVLM0zz999/06pVK9zc3KhQoQIDBgwAoFOnTly7do3XX38dSUoRzNJ3kQL4/PPPCQkJsQ8fOnSIbt26UaFCBXx9fenYsSNHjx7NtI22rFd70a3kbXzjjTeQJImDBw8ycOBA6tatS6NGjZgwYQL79++3zz937lwaN26Mp6cnVatW5ZVXXkGn02W5TzJrP8D06dMJCAjAx8eHl19+GaPRaB/XqVMnxo4dy/jx46lQoQI9evTIcd2hoaG88MILxMbG2vfftGnTgIzZG+Hh4fTr1w8vLy98fHx4+umniYiIyNDmZcuWERISgq+vL8888wzx8fFZbqezYUr+6p++2BakDk5FZoDAQVjMsHUa/DzQKrwGNoaXduZaeDVYDIReDWX+3rV24dXF7RbPP9iCAQ2eoEFAgyJsvEAgKKsoilLssWhpjkmzYsyYMSImTdfmkhyTFhW2a8JuO5CcXGARPbsEeeFKqNVmIGyntd5A/4XQf0GxCK9mi8w/p63Xe71AL/bfWcvdxLt4az1Z+fRK/N39i7wNZRmR+VpGMZhlbDqILfPVx916OuRHfDVmajvgnOKr3fM1E/HVRaNCQiLRZKbR1H+Ku2mcmdEDD5fcX5a///479evXp169egwePJjx48czadIke9C6fv16BgwYwOTJk/npp58wGo1s2LABgFWrVtG0aVNeeuklRo0alad2xsfHM2zYML766isUReGzzz6jd+/eXLx4EW/vtP40qlRdc0wWkGWFqKgotm3bxqxZs/D0zPigSd1tSqVS8eWXX1KjRg2uXLnCK6+8wltvvcWCBQty3d5t27bh5uZGaGgoV69e5YUXXqB8+fLMnj3bPs2PP/7I6NGj2bNnT67W3a5dOz7//HOmTJnC+fPnATLNbpBl2R7k7ty5E7PZzJgxYxg0aBChoaH26S5fvsyaNWtYt24d0dHRPP3003z44Ydp2ujMpC66lx4hvgocSuwN+GMEXE9+gX5wBPT4ALQ5f9k3y2YO3TrEv+H/YjYE4i63AaBGAPRt3AFJkkiIiynCxgsEgrJMkslCwymbHbLu0hiTZkZ0dDSbN29m9uzZIiZNpqTHpEWFPYoVtgOC/GAxWy2vdn0CKFCxETy1FALqFlsT9l6+T0ySCU8XNXHs51rsNVzVLjxZdyBVfKoUWzvKKkJ8LaMkpCqGZQusbJmvcUl5F01N5hTbgZTMVyf1fLVYLQUyE19VkoSLRkU+9GeHsHjxYgYPHgxAz549iY2NZefOnXTq1AmA2bNn88wzzzB9+nT7PE2bNgXA398ftVqNt7c3QUF58yfs0qVLmuFvv/0WPz8/du7cyWOPPZZmnD3zVUrJfL106RKKolCvXr0c1zV+/Hj7/0NCQpg1axYvv/xyngJdFxcXfvjhBzw8PGjUqBEzZsxg4sSJzJw5E1WyH2mdOnX4+OOPc71uFxcXfH19kSQp2/23bds2Tp48SVhYGFWrVgXgp59+olGjRhw6dIhWrVoB1oB46dKl9heFIUOGsG3bthIT6NpsBzLPfE0uSGBRUBRFGLgLio8Lm63VY5OiwdUH+n4BDzyR42xm2czJiJPsO3OYOEMcLnIIHnIbQKJJZV861w8gJfdFIBAIBCUhJs2MK1euoCgK9evn7PstYtKSEZMWFXbP1+Rhe00DIb4KciLuNvw5Aq4lf1BpMQx6fQRa92Jrwt14A8euxwBQzu8mp+7/h1pSMajRIALUIuO1OBDiaxkl0ZgiQNq+2hXEdsDmdeOiTrEd0BmcM/M1u4JbAG5aFXqTit0TO1PeO/8eS/nBXZt7c+vz589z8OBBVq9eDYBGo2HQoEEsXrzYHugeP348zxkEuSEiIoL33nuP0NBQIiMjsVgsJCYmEh4enmFam92A7TyzyOSpK9vWrVuZM2cO586dIy4uDrPZjF6vJzExEQ8Pj1wto2nTpmmmbdu2LTqdjuvXr1O9enUAWrZsWSTrPnv2LFWrVrUHuQANGzbEz8+Ps2fP2gPdkJCQNBkalSpVIjIyMlfrcAbsRfdUGQUpdXI2rIKCRVbs3bQEgiLDYrLaDOz72jpcqRk8tQT8a2Y7m6zI/HnmTyb9/S73I9vj4loLX6kaklwOkGhc2UcIrwKBoNhw16o5M6OHw9adW0pKTJoZIiYtfTFpUWE7U2xJBBr7u40QXwXZcHErrH4JEu9b6w30/QIaP1nMjVAIPW+9hst5GTgVtR2AfvX6U6NcTdGLq5gQ4msZxSa+2vxeAXwKIL7abAc0KlWJ9nwFqyAtSRKSijx1typuFi9ejNlsTlPMQFEUXF1d+frrr/H19cXdPe9f01QqVYZA1GRKe04MGzaM+/fv88UXX1C9enVcXV1p27ZtGs8q+/JsXXOklAClTp06SJJk7xqVFVevXuWxxx5j9OjRzJ49G39/f/79919GjBiB0WjMdbCZG9J3NSvOdQNotdo0w5IkIZcgA39TNpmvKklCrZKwyApmWSGTWncCQeERfQ3+eBFuHrYOt34Zus0AjWuWsyiKwrrzm3l304/culsO14RX8VICUCve9retJlV86VRXCK8CgaD4kCTJqWNRGyUlJs2MWrVqIUlSjkW1RExacmLSIiOd56taFNwSZIfFBDtmw7/zrMNBjeGpH6F8rWJvyvk78dyK1aOSFK4lbQQJutbsSuPAxsXelrKMKLhVRrEV27L5vQL4uBWg4FYa2wGb56tz9t035CS+Jn/pt03njJjNZn766Sc+++wzjh8/bv87ceIEwcHBrFixAoAmTZqwbdu2LJfj4uKCJdmGwUZAQAB37txJE+weP348zTR79uzh1VdfpXfv3jRq1AhXV1fu3btnH5963pSCW9ZhWVHw9/enS5cuLFiwgISEhAztiomJAeDIkSPIssxnn31GmzZtqFu3Lrdu3cp5B6XjxIkTJCUl2Yf379+Pl5dXmi//6cnNujPbf+lp0KAB169f5/r16/bfzpw5Q0xMDA0bNszztjgrti5XmXm+guiaJSgmzq6DRe2twqubLwz62dqtKwvh9VZMEjM3hdJw9leMWZpA/J3BeFv6oFYCUEtQo7wHnesF8OLDIXSuV1FYZggEAkE6nD0mzYly5crRvXt35s+fL2JSQbakZL5a/7VnvoqCW4L0xN6ApX1ShNdWI2HEVocIryaLzO6L1ntiknQKWUrkocoP8XDVdsXelrKOEF/LKEnJma+pxdcUz9f82w5o1RJers6d+Zpdwa3UvxtMziu+2gzwR4wYwQMPPJDmb+DAgSxevBiAqVOnsmLFCqZOncrZs2c5efIkH330kX05ISEh7Nq1i5s3b9oD1U6dOnH37l0+/vhjLl++zPz589m4cWOa9depU4dly5Zx9uxZDhw4wPPPP58mo0HORHxVp+ua8+mnn2KxWHjooYf4888/uXjxImfPnuXLL7+kbdu2ANSuXRuTycRXX33FlStXWLZsGQsXLszz/jIajYwYMYIzZ86wYcMGpk6dytixY+3eWpmRm3WHhISg0+nYtm0b9+7dIzExMcNyunbtSuPGjXn++ec5evQoBw8eZOjQoXTs2JEHH3wwz9virKQU3Mp8n9qPv8W5ritZUUgw5L2qs8DJMBtg4zvw2/Ogj4XKLeF/u6FB3wyTRsbr+WLrRTp/9g/tPtzO4tAEknS1UOGGu6ueJx+syFfPNuOFh0N4vFllmlTxs39UFAgEAkFanD0mzQ1ff/21iElLUUxaVKQPFW22WhZFSfPuIyjjnN8ECx+B6wes9Qae+hH6fJarQq9FwYGwKBKMFmR0JEmnaVChAT1r9UD05Cp+hPhaRrEV3Erdlakgnq82v0cXdWmwHbAK0mZZthcRcjYWL15M165d8fX1zTBu4MCBHD58mP/++49OnTqxcuVK1q5dS7NmzejSpQsHDx60TztjxgyuXr1KrVq1CAgIAKxfxRcsWMD8+fNp2rQpBw8e5M0338yw/ujoaFq0aMGQIUN49dVXqVixon186uRGKZ3tgJw8MiQkhMOHD9O5c2feeOMNHnjgAbp168a2bdv45ptvAKsv1ty5c/noo4944IEHWL58OXPmzMnz/nr00UepU6cOHTp0YNCgQTz++ONMmzYt23lys+527drx8ssvM2jQIAICAjIUR7Buv8Rff/1FuXLl6NChA127dqVmzZr89ttved4OZ0WWFbuonpWfq8YJK8IqikL4/UQu39Xl674ncBKiwmBxdzhgvW/Qdiy8sAnKVU8z2YnrMYz/9Rjt5mxj3tYLhN01oSBjUJ2lVrXTLBlRhzPTnuDTJ1vRoW5F1Nm8CAsEAoHAirPHpLmhZs2aHD16VMSkgmxJ7/mqliSkZAHLLLJfBWYjbJ4MKwZZC70GN4f/7YJG/R3WpNgkE0evRQOQpDpCNb8qPNFgAJIkYlxHICllLN3nxo0bVK1albCwMEJCQhzdHIex5thNxv92nIdrl2f5yDYA7Lxwl2E/HKR+kDebxnfI0/Ie/nA7N2OSWDPmYSyywsBv9lLV353db3XJeeY8YjKZ2LBhA717987gSZQbPtp0jm9CL/PiwzWY0rcher2esLAwatSogZub9YvUudtxGC0ytQK80vjiCnKHwWThfEQ8KknigcrWYPyezsCtmCR83bVULedOXFwcPj4+2X7pFzgnsiynOX5Gs4Vzd6zHu1GwT6Zds29EJxKVYCTQx41AH8d8+U1PdIKR69HWzJDyXq5U9iu+iqN5JbP7VEEo6H3UaTi9BtaOA0McuJeD/t9AvV720UazzMZTt1m69yrHwmPsv+tVZ9GpN9GtYSU+7PYe9SrUS7PYqKgoFuy4hKePX45NSIiL4ZXOtfH3L95KsVevXqVGjRpcv36dKlWqFOu6BYWDiElLNoV9Hy3s+7wgZ9LHM4KSR3Eew/s6AzdjkvBx0xJSwerLe+Z2HGaLTJ2KXriXAH/mwkDEpJmQod7AaOg2Pdt6A0XN/fv36fPlLu4YXDBxC3fvU7zY4kXcNRnfdwoSy4p4NPeUjTuEIAO2glvu2oyZr/nJWE3pcizZrQx0JTTzFay+r0aLjN5kEeJrPrB1vVGpUkS49LYDgtKDLfNdo5ay9MR0Ns9Xk0XmVmyK55rBlL1PmsDJMOnhn8lw6HvrcNU28ORi8LUGfXfjDaw4GM7P+68RGW8AQMFEgnoX8Zq/6VSnJh90+YiWwRkrSgsEAoFAIBBkRepQV6OSMFucJ74VOICz6+CvV6y2V26+0G8BNHjM0a1i27lb3IwxoHJXo3I7x+CmgzMVXgXFh1CVyiiJyQW3PF0zer7mp/ut7YHjolbhlcp2QFEUpytQYjBbRZasPF9t4+Jx7qJbzowt/kilvabYDpStZPsygf3jSzYZBzY7Amew8lAUhZvRSVhkBY1KhVmWxbVekrh/GVYOgzsnrcOPvA6dJ4Nay8kbsSzZG8a6E7cxJp9rshRDnHod8ZpNPFS1PnMe/Y5OIZ0c136BQCAQCAQlDtsrjJTKK1MjkkvKLmYDbJkCB5L9lys/CE8tAb9qjm0XkGQ08e5fBwAvzOqLDGnaD1/XjNYwguJFiK9llASDreBWyingkyya6gxmzBYZTRaFczLDZE4ptmMrTGKWFfQmGfdURb2cgdxlvlrH6UU2XL6wZ76mEt5V9uDEIU0SFCG2zFdtFn6v4Fyer7FJJuL0JiRJolp5D67c1WGyyFhkWfh8Ojsn/4C/XwOjDjzKw4BvMdXswqZTd1i69ypHkn2tAGTNFe5Lf5Co3kujivWY3WUpj9d73Ok+CAoEAoFAIHB+lGTX19RhhNqJ4ltBMRJ1BVa+ALePW4fbjYNHp4LaOWwTBi75BoOhIjJJ9GvciECvIEc3SYAQX8ss9szXVMKoj3vKzSJeb6acp0uul2fLMNKoJTy0aiTJ+nUwXm9yWvE1u8xXt+SiWyIbLn9kJr7aMl/Fl+HSh1m2Xf/ZZL7axHcHFyQwW2RuxegBqOjtiperBo1ahdlizX71cBHiq1NiSoKNb8PRH63D1R+Ggd+z5rLChx/t4E6c9ZiqVQqy6xFuyb9gVF0gxC+EGZ1+4LnGz6FWOdezSCAQCAQCQckhswjWbqslCm6VHU6vhrWvJtcb8IcBC6FuD0e3ys70bV9yKqwyYKJBsJo65Ws6ukmCZIT4Wkaxeb56pBJGtWoVni5qEowWYpNMeRJfbd2OXdQqVCoJL1cN8Xoz8QYzeas3WvTYhOJsM1+Tx1mz4RT7V01B7kjW4tLaDiTvbmE7UPrITearWu0cnq83Y5IwyzJuWjUB3lYTfDeNCp1FxmCS8cj9bU9QXNw9DyuHQ+QZQIIOE6Hj2/xy+BbvrrZaD3i7KxhdtnPZsBQL0QR6B/Jeh68Y1WIUrg4sdiAQCAQCgaB0YLcdSO35qrYll4iEnVKPSQ+b34XDi63DVdvAkz+Ab2XHtisVv576la+338KTWgSUi6VT7UaObpIgFUJ8LaMkJGe+eqQrJuXrrrWLr7nFIit2j09tssDi46a1iq9OWHTLYMo581WjVqXygrSksWcQ5IxNYE0tWqtSeb4K+bV0Ybak2I5kRYrtgOwwL+jYJCOxSSYkJKqWc7efk64aFToD6M3CZsTpOL4C1k8AUyJ4VoQnvoVanVlxMNwuvHr5HeKUfjYYzfi4+fBWu1m81uY1vFy8HNx4gUAgEAgEpQXb+0tqz1dhO1BGuHfJmggQYas3MCG53oDzaAShV0MZ9ccnlLfMABS+eKoL289FOrpZglQ4z9kiKFYSkz1fPdNZAvi4a7kVq8+T+GpKZeKpTRY0vVxtRbfyXryrqMlN5itYfV/NBpENlx8ytR1IJcTKIkApVdgyXzXZFdxKdfzNspJtlmxRYLbI3Iy2dk0P8HbBPdUHFVdtss2ISWQtOA3GBNgwEY4vtw7X6ABPfA/egfx6MJxJq6zBb5z6L67pv8NN68arD03g7Ufext/d34ENFwgEAoFAUCpRMnq+OlNNA0ER8d9KWDc+ud5ABXhiEdTu6uhWpeFkxEn6rxiIt2EmAEPaVKd+JR8hvjoZQnwtoyQmF5JyT5fRafN9jcuDaJpafLU9gLxtxbucMfPVVnBLnb3/n5tGRYLIhssXtvgjte2AJEmoJAlZUbAI64FSRUrma9aCqiRJaFQSZlnBIitoi9l+83asHrMs46pRU9HbLc04Wxa88Hh2EiLOWLML7p0HSQWdJkH7N0Cl5osdh5m3OQKwCq9xLj/wv5b/4/0O71PZx3m6fQkEAoFAIChdpGS+puAsNQ0ERYAxETa9DUd/sg6HtIcnvgOfSo5tVzqux16n1/JeyImP4KJUx89Dyxvd6yHrdY5umiAdQnwtoyQaMhbcAqvtAJDHzNeUh42t27FNfHVG2wFbwa2cM19FNlx+sWW2qtJ55apVErJFQdgilR4scoqYnl3BLQC1SoVZtljF2mJUX+OSTEQnGpHAajeQ7rx0TS6wZzTLyIqSJmNbUIwoChxbBhveAnMSeAXBwO+hRntuxt3kpd+XcvpSM8AqvPZormNml3PU9q/t2HYLBAKBQCAo9SiZqK9qlXPUNBAUMunrDXR8Czq+DU5WvDVGH0Ov5b24HZdAVfMQAN7qUR8/Dxei9A5unCADoqxzGSXBVnArneerj1vexVdb1ptaJdm7lnu55T2DtriwZbdl5/maenxZzIabNm0agYGBSJLEmjVr8jx/ZrYDqYeLOvM1NDQUSZKIiYkBYOnSpfj5+dnHT5s2jWbNmhVpG9LTqVMnxo8fX6zrLA7s178k5ViYzlaUoDgDVLMsczMmCYAK3q4Z7nlgzdhVSRIKiv3jjKCYMcTDqpdg7Tir8FqrC7z8L/cDGzLxn4k8MPclTl1qAkD58v+xfewrrHjyFyG8CgQCQSmnoDGpoxExaekhM8/XlIJbCoro2Vc6OP4LfNvJKrx6VoSha6Dzu04nvOrNevr/2p/Td08TzMuguNO4si+DWlV1dNMEWSDE1zJKkq3gVhaZr3FJuc9YNWbS5dhuO2BwxsxXq/CcU+armz0bzmIXE52J4cOHI0kSkiTh4uJC7dq1mTFjBmZzwfb52bNnmT59OosWLeL27dv06tUrz8tIbztgCyxt4lx2nq9xcXFMnjyZ+vXr4+bmRlBQEF27dmXVqlX5DmoGDRrEhQsX8jVvXkkfZNtYtWoVM2fOLJY2FCd2v9ccsl7BMb5Yd2L0mCxWu4HAdHYDNiRJwlVr+9gibEaKnTsnrUHuyd9BUsOjU9E9/SOzji6i5pc1+Wb3cXz0LyOhontjFw6/+Q7NKjVzdKtLHN988w1NmjTBx8cHHx8f2rZty8aNG+3j9Xo9Y8aMoXz58nh5eTFw4EAiIiLSLCM8PJw+ffrg4eFBxYoVmThxYoZnTmhoKC1atMDV1ZXatWuzdOnS4tg8gUDgQJw5Jk1PXsROEZMKUqNk4vlqe7dRsNpqCUowxgRYPRrWjLYWeq3REV7+F2p2cnTLMiArMsPWDGPntZ34qZqh1j8CwPR+jXJMhhE4DmE7UEaxZ74Wou2ANlWxHae2HchlwS2NWkItSVgUazacW3GbVOaCnj17smTJEgwGAxs2bGDMmDFotVomTZqU52VZLBYkSeLy5csA9OvXL98V6bPKfLU9DCyKkumXn5iYGB555BFiY2OZNWsWrVq1QqPRsHPnTt566y26dOmSJlsgt7i7u+Pu7p7n+VJjNBpxccl/5TV//9JZBMgk5+z3asMuvhaTL1a83kRUohGAKpnYDaTGTaMmyWix2owU7FQR5BZFgcM/wKZJYDGAT2WM/b9h4d0TzP6qDpEJkXiaH6WC6VVAxdC21Zn+eKN835fKOlWqVOHDDz+kTp06KIrCjz/+SL9+/Th27BiNGjXi9ddfZ/369axcuRJfX1/Gjh3LE088wZ49ewDrM6JPnz4EBQWxd+9ebt++zdChQ9FqtXzwwQcAhIWF0adPH15++WWWL1/Otm3bGDlyJJUqVaJHjx6O3HyBQFDEOGtMml9ETCrIQHL4mvpMVCX3/LLICmZZQeN8r4uC3BBxBlYOg3sXkusNvAvtJzhdtquNN/95k99P/45WcqGZx2zCEhQGtqhCi2rlHN00QTaIzNcySorna/qCW9bhuDyJr8niSyox09vVJr46n+2A3fM1u0w9RUEyJeKGAcmUiD4hzvo1rKj/8vgV3dXVlaCgIKpXr87o0aPp2rUra9euBcBgMPDmm29SuXJlPD09ad26NaGhofZ5bd2e1q5dS8OGDXF1deXFF1+kb9++AKhUqjSB7vfff0+DBg1wc3Ojfv36LFiwIE1bbty4wbPPPou/vz8NqlXk2d6dOXr4EEuXLmX69OmcOHGCmgFeNK1ajuXLfsp0e959912uXr3KgQMHGDZsGA0bNqRu3bqMGjWK48eP4+XlBcCyZct48MEH8fb2JigoiOeee47IyKyrOabv4mVj0aJFVK1aFQ8PD55++mliY2Pt44YPH07//v2ZPXs2wcHB1KtXL8d1X716lc6dOwNQrlw5JEli+PDhQMYuXtHR0QwdOpRy5crh4eFBr169uHjxYoY2b968mQYNGuDl5UXPnj25fft2ltvpCFKKbeUi81Vt88Uq+q79FlnhZnSy3YCXK56Z2A2kpizbjDgEfRz88QKsnwAWA0qd7vz6yFjqrh3Ga5teIzIhkhquzxBgGg+oGCaE1yyJj48nLi7O/mcwGDKdrm/fvvTu3Zs6depQt25dZs+ejZeXF/v37yc2NpbFixczd+5cunTpQsuWLVmyZAl79+5l//79APzzzz+cOXOGn3/+mWbNmtGrVy9mzpzJ/PnzMRqtHzkWLlxIjRo1+Oyzz2jQoAFjx47lySefZN68ecW2PwSCUoWiFE/8WYpjUk9PTx588EEOHDiQJiaVJAm1Ws0vv/yS6faImLTkxaRFjd12IF0oYi+6JTJfSx6KAkd+hO86W4VX70ow7G/oONFphde5++Yyb781rhrT+GfC7ip4uWp4u1c9B7dMkBMi87UMoigKiabsM1/z4tVqytR2wLoc57QdyIXnqykRPgimVjG1yc67t8DFM9+zu7u7c//+fQDGjh3LmTNn+PXXXwkODmb16tX07NmTkydPUqdOHQASExP56KOP+P777ylfvjyVKlWiU6dOvPDCC2kCquXLlzNlyhS+/vprmjdvzrFjxxg1ahSenp4MGzYMnU5Hx44dqVy5MmvXrsWg9ebo0aOAzKBBgzh16hSbNm3ipz/WEpNoomZwQIa2y7LMr7/+yvPPP09wcHCG8bYgF8BkMjFz5kzq1atHZGQkEyZMYPjw4WzYsCHX++rSpUv8/vvv/P3338TFxTFixAheeeUVli9fbp9m27Zt+Pj4sGXLllytu2rVqvz5558MHDiQ8+fP4+Pjk2V2w/Dhw7l48SJr167Fx8eHt99+m969e3PmzBm0Wq39+Hz66acsW7YMlUrF4MGDefPNN9O00dGk2A7kLIqpizE4vRObhNEi46JREeiTud1AamwF9vQmYTtQ5Nw6BitfgOgwFJWGU40H8uytfzm98Q8Agr2D6V/tQzYc8UcBhratzjQhvGZJw4YN0wxPnTqVadOmZTuPxWJh5cqVJCQk0LZtW44cOYLJZKJr1672aerXr0+1atXYt28fbdq0Yd++fTRu3JjAwED7ND169GD06NGcPn2a5s2bs2/fvjTLsE0jvAUFgnySHI86hFISkwYFBXH06FFkOW1MunXrVmRZzvTZImLSkhmTFjUp3yPS9+xTAbIoulXSMMTDutfh5ErrcO2uMGAReFZwbLtSIctyGtuQVWdX8cbaNwCY9PAM1u9TYUmKZ1T7umhMiURFJeLn54dKJXIsnREhvpZB9CbZ/vBIX3ymQLYD6pJhO5BScMs5v2blB0VR2LZtG5s3b2bcuHGEh4ezZMkSwsPD7UHjm2++yaZNm1iyZIm9i6jJZGLBggU0bdrUvizb1/igoCD7b1OnTuWzzz7jiSeeAKBGjRqcOXOGRYsWMWzYMH755Rfu3r3LoUOH8Pf350JEPAGVq1Ojgifublq8vLzQaDRUqlQJTbwBFzdXIG121r1794iOjqZ+/fo5bu+LL75o/3/NmjX58ssvadWqFTqdLk1AnB16vZ6ffvqJypUrA/DVV1/Rp08fPvvsM/u2e3p68v3336fp2pXTum1duSpWrJhldzRbgLtnzx7atWsHWF8mqlatypo1a3jqqacA6/FZuHAhtWpZPwOMHTuWGTNm5Gr7igv7x5dcPOSLy3ZApzdxPyHZbsDPPVfeR6kzXxVFEUJfUaAocPBb+Oc9sBhJ8gxgrIcHP/z3HQDl3Mox6ZFJVNEO5N3VZ1EUGNJGZLzmxJkzZ+z3MbBmn2XFyZMnadu2LXq9Hi8vL1avXk3Dhg05fvw4Li4uGe5ZgYGB3LlzB4A7d+6kEV5t423jspsmLi6OpKSkAne1FQgEzo+zxaQAtWunFGe0xaRBQUHIskxcXFyGbRAxacmMSYsahYyer5C6poHoPVViuP2ftQfW/UvJ9Qbeh3avgZOJljExMcxddww3T2+ux4Xz++kteCsDaVmpBcfONiMqMQ4/dw1xSSYW7LiEPiGeCY81F9YiTooQX8sgCcYUQdQ9nY+pT77E14zdjr2SRd04JxRf7bYD2WW+aj3g3VvEJZm4FpWIm1ZNnYq5C6AKhNYjT5OvW7cOLy8vTCYTsizz3HPPMW3aNEJDQ7FYLNStWzfN9AaDgfLly9uHXVxcaNKkSbbrSEhI4PLly4wYMYJRo0bZfzebzfj6+gJw/PhxmjdPudFn5flqG5ZlJYPpSV4KFxw5coRp06Zx4sQJoqOjkZODnfDw8AxZYFlRrVq1NIJF27ZtkWWZ8+fP2wPdxo0bZ/DUKox1nz17Fo1GQ+vWre2/lS9fnnr16nH27Fn7bx4eHvYgF6BSpUrZdmVzBOY8ZL6m2A4UnfhqkRVuxFjtBvw9XfBKzsLPCReNCgkJWVEwWRRcNELsK1SSouGvsXBuHQD/epajb8JlYhLBQ+vB621e5812b7LttI43/zhhF15n9BPCa054e3vj4+OTq2nr1avH8ePHiY2N5Y8//mDYsGHs3LmziFsoEAjyTXI86rB15wFnjUnzg4hJS2ZMWtTYTov0UYm9Z1cx1TQQFABFgcOLYdO79noDPPkDVGvj6JZliZunNwlqA2uubkBx09CoQmPaVnuMFQevo3b3plvzynj55u1+LXAMQnwtgyQarN1q3bXqDBlh+cp8NWdjO+Bknq9yshk65CC+ShK4eOKqsqDEg16SULQeTicCdO7cmW+++QYXFxeCg4PRaKyXtE6nQ61Wc+TIEdTqtAJ76q/w7u7uOW6TTqcD4LvvvksTmAH2ZafPZrJ9+E2fcJi64FZ6AgIC8PPz49y5c9m2JyEhgR49etCjRw+WL19OQEAA4eHh9OjRw+47WFh4eqbtblec6wbsXb1sSJKU7+q6RUVKwa08ZL4WYWZARJweo1lGq1ZRyTdnuwEbKknCRaPCYLZgMFtyLMgnyAM3jsAfwyEmHBMSb5DEVwnX0Kq1jHvwZSa3n0ygVyCrj92wC6+D21QTwmsRYKtCDtCyZUsOHTrEF198waBBgzAajcTExKTJjoqIiLC/+AcFBXHw4ME0y4uIiLCPs/1r+y31NNl1dxUIBNmQHI+WBJw1Js0PIibNSEmISYuLDJmvalt8Wzb3R4lBHwtrX4Uza6zDdXtC/2/Aw7mzROONcay4+AcGi4FqvtV4rG5//jp2BwWoHeBJVf+SJ7zu2rWLTz75hCNHjnD79m1Wr15N//79M5325ZdfZtGiRcybNy+NjVVUVBTjxo3j77//RqVSMXDgQL744os0z5X//vuPMWPGcOjQIQICAhg3bhxvvfVWEW9d1oi3yzJIosmajZre7xVSeb4mmXL9QDXJJcd2wGhJEX1yI664qFX24CL1vM6Cp6cntWvXplq1avYgF6B58+ZYLBYiIyOpXbt2mr/UXbdyQ2BgIMHBwVy5ciXDsmrUqAFAkyZNOH78OFFRUUDGzFcXFxcsFgtqKWvPT5VKxTPPPMPy5cu5dStjlodOp8NsNnPu3Dnu37/Phx9+SPv27alfv36+vryHh4enWc/+/ftRqVT2IgaZkZt127ISLJasvUMbNGiA2WzmwIED9t/u37/P+fPnc52p4CyY7bYjuch8TeX5KhdBwJ5gMHNPZ7WzqFLOPdmDK/e4aZOtB0zOd62XSBQF9n6N8kN3iAnnMjJtiedrycSwZsO4MO4CX/b6kkCvQP46fpM3frcKr8+3rsaMxx8QwmsxIMsyBoOBli1botVq2bZtm33c+fPnCQ8Pp23btoA1E+vkyZNp7nlbtmzBx8fHft9q27ZtmmXYprEtQyAQlF6cNSZNjy0mzQ4Rk5bMmLSosRfcSpf7KgpulQBuHoVFHazCq0oD3WfDs786vfAaq49l5ek/iDPGU8GjAk81HMTGk5FExhtw1ajoUDdjHZWSQEJCAk2bNmX+/PnZTrd69Wr279+fqff2888/z+nTp9myZQvr1q1j165dvPTSS/bxcXFxdO/enerVq3PkyBE++eQTpk2bxrffflvo25NbhPhaBklIznz1cM1afJWV3BfLSsl8dX7xNbWokm3BrWQkSUrxgixBgkzdunV5/vnnGTp0KKtWrSIsLIyDBw8yZ84c1q9fn+flTZ8+nTlz5vDll19y4cIFTp48yZIlS5g7dy4Azz77LEFBQfTv359///2X8KthbN2wloMHrFWyQ0JCCAsL49TJE0RH3SdJr890PbNnz6Zq1aq0bt2an376iTNnznDx4kV++OEHmjdvjk6no1q1ari4uPDVV19x5coV1q5dy8yZM/O8TW5ubgwbNowTJ06we/duXn31VZ5++ulsXwRys+7q1asjSRLr1q3j7t279iyN1NSpU4d+/foxatQo/v33X06cOMHgwYOpXLky/fr1y/O2OAqLkiKianIhdKpVKeFqYQeosqxwI9pqN1DOw8WefZ8XUnxfRdGtApMYheHnJ+CfyUiymZWYaIGOqg0e5+Tokyztv5QQvxAA1p64xeu/HUdW4NmHqjGz3wOocuHTK8gbkyZNYteuXVy9epWTJ08yadIkQkNDef755/H19WXEiBFMmDCBHTt2cOTIEV544QXatm1LmzbWrnjdu3enYcOGDBkyhBMnTrB582bee+89xowZY/eZffnll7ly5QpvvfUW586dY8GCBfz++++8/vrrjtx0gUDgQBwZk+7Zs4crV67w559/sm/fPiAlJj1+/Dj37t3DYDBkuh4Rk5asmLQ4sCUmpf82bPvYLzJfnRBFgf0LYXF3iL4KvtXgxc3QbmzGA+lk6M16Bq8azL2ke3i7ePFc4+fZcTaGG9FJaFUSA5pXztf7jjPQq1cvZs2axYABA7Kc5ubNm4wbN47ly5dnyLw/e/YsmzZt4vvvv6d169Y88sgjfPXVV/z666/2D1nLly/HaDTyww8/0KhRI5555hleffVV+7PCEQjxtQySmOz56umS0XXCVaPCJVlEza31QIrna0bbgSSTBbMTZYwakr/8SlLKV8qccEsWZPQlTJBZsmQJQ4cO5Y033qBevXr079+fQ4cOUa1atTwva+TIkXz//fcsWbKExo0b07FjR5YuXWrPMnBxceGff/6hYsWK9OnTh4HdHuaH+Z/bMx8GDhxIz549ebxXdzo1rc3aVX9kuh5/f3/279/P4MGDmTVrFs2bN6d9+/asWLGCTz75BF9fXwICAli6dCkrV66kYcOGfPjhh3z66ad53qbatWvzxBNP0Lt3b7p3706TJk1YsGBBtvPkZt2VK1dm+vTpvPPOOwQGBjJ27NhMl7VkyRJatmzJY489Rtu2bVEUhQ0bNmR4uDgztqxXtUrKlVgmSVJKgFrIvlgR8XoMZovVbsAv93YDqbEV4dObneeeVRLRXdpGzBeNcb28HT0Ko0nim5DW/DNyP6sHraZRxUb2adf/d9suvD7Tqiqz+wvhtaiIjIxk6NCh1KtXj0cffZRDhw6xefNmunXrBsC8efN47LHHGDhwIB06dCAoKIhVq1bZ51er1axbtw61Wk3btm0ZPHgwQ4cOTVNwpUaNGqxfv54tW7bQtGlTPvvsM77//nt69OhR7NsrEAicB0fFpL1796Zx48Z8+OGHdlsCW0zauXNnAgMD+fPPPzNdj4hJS1ZMWhxkFbmmFJQV8aNTkRQNvw2GTW+DbIL6j8HLu6DKg45uWY7IisywNcPYe30vrmoXnmv8PAcv67lyLwGVBI83CybQJ3/vO0VFfHw8cXFx9r+sPmzlBlmWGTJkCBMnTqRRo0YZxu/btw8/Pz8efDDlWHbt2hWVSmXP4t+3bx8dOnRI45Xdo0cPzp8/T3R0dL7bVhAkpYyZtdy4cYOqVasSFhZGSEiIo5vjEDafvsP/lh2heTU/Vr/ycIbxD87ayj2dgQ2vtqdhcM5FPP46fpPXfj1Ou1rl+WWUNUPGZJGpM3kjAMendMPPwyW7ReQJk8nEhg0b6N27d56DghvRiTzy0Q5cNSrOz+oFWCuMhoWFUaNGDdzcMt7EIuL0RMTpKefhUiI9VYobs0XmzG1r5djGlX3TdB1OMpq5GKmzCmTuMj4+PqicrKqkIGds1YFVrp5cvZ+Am1ZN3UDvXM17ISIevclCjQqehfa1NtFo5nKkDgUIKe9pLxyYn+VcitShUalyde8rTnK6T+WVgtxHsyLJmMChlUNod3EbGuACFqYH1GB4z7l0rdk1g43AxpO3GbviGBZZ4amWVfhoYBOnEV6joqJYsOMSnj5+OU6bEBfDK51rF3tl2atXr1KjRg2uX79OlSpVinXdgsJBxKQlm8K+jxb2fV6QM7Z4RsSjJZfiPIaXInUkGs1UL+9p7y0KkGgwc+muDhe1ivqVnCt+LApKQkzKjcOw8gWIDQe1C3SfBQ+95PTZrjYmbJ7AvP3z0Og1DK/zC5GJlThxIxYJeKxJJWoGZF4IPHVMWlyxrC0eTc/UqVOZNm1ajvNLkpTB83XOnDns2LGDzZs3I0kSISEhjB8/3u75+sEHH/Djjz9y/vz5NMuqWLEi06dPZ/To0XTv3p0aNWqwaNEi+/gzZ87QqFEjzpw5Q4MGDfK8rQVFFNwqg2SX+Qrg667hns6Q68zXFM/HlAeeVq3CTatCb5KJ15sLVXwtCMbkjLa8FNNJ6YosvmbmhtR+r+nFFpXwRCpVmPNQbMtGStGtwjkHZEXhRlQSCuDn4ZJv4RVSMl/NsozZIqPJw3aVZcyymRX7v6Ly9pl0Se4hsM7VHUvvT/m5yfOZerduOnWHccnC6xMtKvOhEwmvAoFAIBAIBOlRknNf00cralFwy3lQFNj3NWydBrIZyoXAU0shuLmDG5Z75u6by7z98wCY32c+Gw76cCIyFoDujQKzFF4dzZkzZ6hcubJ92GZJlVeOHDnCF198wdGjR0td/QchvpZB7J6vmRTcAuziRUFsBwC8XLXoTQan8n21Cag2kSU3uGmt0xpMFhRFKXU3gcLGFneoMtlPtoJbsqJQtnLuSycmi83vNffXRErXrMI5ASLjDOjNFjQqFcG+Bfv6rlZJaNUqTBYZg1mIrzkhKzJ/nPmDNZvf4pO4+1RGhR443GwQPfvOR6POXAj/5/Qdxv5yFLOsMKB5ZT55silqIbwKBAKBQCBwZpJD1/SvOLbYVlYUZFkRH5MdRWIUrBkNFzZZhxv2h8e/BDdfhzYrL/x66lfe+OcNAD7u+jFJMQ9y5NoF1O7edK4XQP0g582s9vb2xsen4O3bvXs3kZGRaWxpLBYLb7zxBp9//jlXr14lKCgoQ4FBs9lMVFSU3Ss7KCiIiIiINNPYhvNa7LGwEG+WZZAkY/biq60bRZw+r+Jr2tPJx150K3fLKQ6MdvE196e+i0aFhLW4UGH7VJZGbFmtmcUdqYMR8XG45GPO4trPDpugaZELnklutsjcjbf6CVX2cysUsVRkuueMoihsurSJhxa15L+VQ1gWF0VlVER5VkB6aQeP9P82S+F165kIxiQLr/2aBfPpU0J4FQgEAoFA4PzYXl3SRy2pe/uJ7FcHEb4fFra3Cq9qV+gz15rxWoKE19CroQxbMwyAcQ+No5rLID795wIAbWv606SKnwNbV3wMGTKE//77j+PHj9v/goODmThxIps3bwagbdu2xMTEcOTIEft827dvR5ZlWrdubZ9m165dmEwpWtSWLVuoV68e5cqVK96NSkZkvpZBEpJtBzxcs7IdSBZfc5n5aszEdgDA2y6+Ok/mq9GSd9sBlSTholFjMFvQmy1o8zBvWcRmI53ZV1+VJKGSJGvma3E3TFDomOzXfu7FM3UhZr4mmSwoKLhq1PgWkrWJm1aNzmDGUMIK7BUXe6/vZdK2SZy7upufcacb1mxj0wNP4t/3C3DNuivUjnORvLL8KCaLQt+mwXwmhFeBQCAQCAQlBHuvvXSpr5IkoVFJmCwKZlnGReS3FR+yDHs+h+2zQLGAfy2r6FqpiaNblidORpyk/6/9MVqMDGwwkB6V32bciuMANK3iy0M1ireuQFGj0+m4dOmSfTgsLIzjx4/j7+9PtWrVKF++fJrptVotQUFB1KtXD4AGDRrQs2dPRo0axcKFCzGZTIwdO5ZnnnmG4OBgAJ577jmmT5/OiBEjePvttzl16hRffPEF8+bNK74NTYcQX8sgicmZr55Z2Q645c12IKvsN69k8VVncCLx1eb5mkmGXHa151w1KgxmCwazTO7KCpVdLNnYDoBVfJMtish8LQXYPF/zknFamJ6vtix+d23ubURywp75anKuzFdH18b8L+I/Jm+fzLoL6+isqDmBF0FIKFp3pN6foW3+fLbzh56P5H/LjmC0yPRpXIl5TzcVtg4CgUCQCY6+3wsEgszJyvMVrO83JkvZqGvhNPeohHuw+n9waat1uPFT8Ng8cC1Zb+vXY6/Ta3kvYg2xtK/WntFNvmD0sv+QFXiieWUCvF3I/KwruRw+fJjOnTvbhydMmADAsGHDWLp0aa6WsXz5csaOHcujjz6KSqVi4MCBfPnll/bxvr6+/PPPP4wZM4aWLVtSoUIFpkyZwksvvVSo25IXhPhaBrEV3PLIsuBW4Xi+ertal+NMtgO2bLbUma+2qoqJiYm4u7tnOp+rVgV6q++rIHvsma9ZPCNUdt/X4mqRoKjIT+arTXArFPE1+Xp0dyk8Ec/mB613sszXxMREgMKrAptLrkRfYcqOKfxy8hckRWEGbky25XQENEB6ailUrJ/tMnZduMtLycJrrweC+PyZZkJ4FQgEgnTkJh4VCAQOJAvPVyj8grLOjKNi0jRc/Rf+HAnxt0HjBr0/geZDMj84TkyMPoZey3txM/4mDSo0YPrDy3hl2Ul7ssJ7PaqzaOdlRzez0OnUqVOeRPyrV69m+M3f359ffvkl2/maNGnC7t2789q8IkOIr2WQxBwKbhW27UCcM9kOZOL5qlar8fPzs5s2e3h4ZCiqpbKYUMxGEpIs6N2FaJAdSUlGFLMRRS2j1+szTmAxopgtGE2g1+tRqcT+LGnIsozBYMRkkFBQMBuN6OXcXecWkxnFbMSomNHrC/YISkhMQrHIqGQ1mZ1q+UGxyNb2mSExUevwogmKopCYmEhkZCR+fn6o1YWX5Zsdt+NvM2vXLL49+i1m2UwlRWKLZwiNEqKsEzQfAr0+BhePbJfz78V7jPrpMEazTPeGgXz5bPM8eQQLBAJBWSE38aigcJFlGaPRKOLREkxxHkOLyYgiyxj1elRyuhjWbEIxm0hKUuGucq7eU4WFo2LSNMgW2P0ZhM4BRYYK9aw2A4ENi78tBURv1tP/1/6cvnuaYO9g5ndfzWvLz5FkstChbgDzBjVDFxfj6GYKChEhvpZBcvJ89XG3/p73zNfMbQecyfPVVkQnveerreJd+qp5Noxmmch4A2oVWGJFNkJ2xOvNxCaZ0LmoMcZk9OG8pzOgN8kkahR00e7ixaIEoigKCUlJxBgkJECb6Jbr42i2yETGGVBJIOnyfy3JisKtGKviqklwK1SR9F5MkjUzW+fqNEKhn59fsVTmjE6K5uM9H/PFgS9IMicB8G6lNkyLuoU2IQq0ntD3c2jydI7L2nvpHiN/OoTBLNO1QSBfP9fCafanQCAQOCM5xaOCwkVRFJKSknB3F/FoSaU4j2FETBIWBaRM4sOYRBM6g5kkNw2x7g7MCC0GiismzUB8BKwaBWE7rcNNn4M+n4KLZ/G3pYDIisywNcPYeW0n3i7efN/rLyb+dp04vZkHq5dj4eAWeapRIygZCPG1DJKT52tebQfsnq+adLYDyd6xOoPz2A4YsxBfJUmiUqVKVKxYMU1FPBsJRjOvfPUvAKtfaYePe+EU9ymNLNt3laV7b9KncSUmdK+RYfxPf59m14W7dK8sM2Fge8d2WRHkC5PJxO+bd/HDeTV+Hi78ObpdrueNTzLx8l97ANjwantc8+nXevx6NNN2nKCitxsrXircr91zfznKmdtxvPdYQzrXrlioy84PWq22yLMLEowJfHngSz7e+zEx+hgAHqnchuXlGlLt5B/WiQIbW7MLKtTOcXn7r9znxR8PoTfJdKlfkfnPNxdBpEAgEORATvGooHAxmUzs2rWLDh06iHi0hFKcx/C1r/8lwWBmyQutqOafVvD7ae9Vftx3K8v3n9JCccSkmXIlFP4cBQmRoPWAPp9Bs+eKvx2FxJv/vMnvp39Hq9KyuM8qZv0Vxz2dgYaVfFg8vFWW9pCCko04qmUQm/iale2Aj812IJcZq3bfx3RdPXycOfM1i+wrtVqd6QPFzQ0UlZZbsXrCY808WM6nSNtZkrmvh5vxFsySFjc3twzjZUnLzXgLkQkW3NzcRLBbAlGr1UToLNyMBz/vzI9zVri6uhKRIGOWFRIsKny9cz9vak7dSeJmvIUHqnnlaf25wc/bk5sXojl/V0+vpoW7bGfDaDHy3fHvmLlrJnd0dwB4oOIDzG3zBl2P/YpkE14ffBF6fADanLOVD1y5zwtLrMJrp3oBfDO4hd1LVyAQCAQ5k1U8Kihc1Go1ZrNZxKMlmOI8hjfizCQaLbi6umWIPd093LkZb+FarKnQ49IyjWyBnR/Bzo8BBSo2tCYCBNRzdMvyzdx9c5m3fx4AX/f8kYVbNNyMSaBGBU9+fPEheyKcoPQhxNcySIKhcAtuGbOyHXB1PvHV7vmaj2y7WhW9uBWr51KkjgdD/Au7aaUGW0E3T9fM97HNCzjJIrp3lWTijNZ/g3zyFmBKkkR5Lxci4gzc1xkJ9suf9cCZW3EANAr2zdf82VG7ohcAlyJ1hb5sZ8EiWwiNCmXCoglcibkCQA2/GszoPINnXSugXjMakqLAxRse/xIeeCLHZcqywo7zkYxbcczuV7VwcEshvAoEAoFAICjx2IppZVY0tLyntVdkVIKxWNtUqom7bS2qdc3a+5QWQ6HnRznWG3Bmfj31K2/88wYA09t/xpq9Vbh8N45gXzd+HtmaAG9XB7dQUJQI8bUMYrcdyEIc83HLm/hqMudgO+BM4qsl+8zX7Khd0YvdF+9xsRQLMoWB7fxyzyKz2nZeONFpIcgHscmxZcU8iq8A/p6uRMQZuJdgyPf6T92KBeCByoWfhW4TXy/fTSj0ZTsaRVFYd2Edk7ZN4vTd0wAEegYypeMURjYdhkvoh7B3jHXiSk2t2QX+NbNd5uW7OlYfvcnqYze5GWP1iW1fpwLfDmmJWz5tJQQCgUAgEAicCbvVXiZ1Bsp5CPG1ULm0FVb9DxLvgYsXPPY5NHnK0a0qEKFXQxm2ZhgAo5pMJPRYC67cjaOClwvLRramcj4TUgQlByG+lkHs4pg2i8xXD6s4ZjTL6E2WHF+ebV8B0wuatgzHOL3zeFZl5fmaG8pCNlxhkGT3FM78/ErJfC22JgmKgFiTNfAM9Mn7F9oKXskBqi5/AWqS0WK/Dosi87VWgPVav3JXh0VWUBdiMS9HsvPqTiZtm8S+G/sA8FR78k77d3i97et4Jt6Hn/rBjUPWiR/6H3SfCZrMj290gpG//7vFqqM3OX49xv67t6uGAS0q827vBkJ4FQgEAoFAUCqQZYXkV95M48LyXkJ8LRQsZtgxC/61dsvPS70BZ+ZkxEn6/9ofo8VInxovcOp8D27FJNgzXmsmv3sISjcOr34xf/58QkJCcHNzo3Xr1hw8eDDb6T///HPq1auHu7s7VatW5fXXX0ev1xdTa0sHOXUL93LRYHumxOUi+9WWTapJ9yDyckLPV7vtQD7E1zoVvQEhvuZEQvL5lXXmq/W80AvxtURjy3wNzEfmq61r1v18Zr6euxOHrFhF3IpF0D2nqr8HLhoVBrPMreRMzpLM0dtH6flzTzr92Il9N/bhrnFnYtuJLGqwiLfbvY3nlVBY+IhVeHX1haeXQe+PMwivBrOFTadu89JPh3nog61M+es0x6/HoFZJdKlfka+fa86h97oyo98DQngVlEhETCoQCASCzLAlG0HmtgO2zNeYJBOWVNMK8kDcTVjaJ0V4bTUSRm4t8cLr9djr9Frei1hDLK0rPsHta89wK0ZPzQqerBzdTgivZQiHZr7+9ttvTJgwgYULF9K6dWs+//xzevTowfnz56lYMWOF6V9++YV33nmHH374gXbt2nHhwgWGDx+OJEnMnTvXAVtQ8pBlJVXBrcwPv0ol4e2mJTbJRGySKcduxSm2A5kX3NIZnEd8NZit254f8dWW+XozJolEo1lUIcyCnAq62WwHksylI5uwrBJrzH/mq7+ndZ77+cwOOJ3K71WSCv88Uqskalbw5NydeC5F6qjqXzK9pS7cv8D7O97n99O/A6BRaRjVYhTvd3ifCm4V2LhuLap/JsOhRdYZKreEJ3+AciH2ZSiKwtHwGFYdvcG6/26nsaN5oLIPA5pX4fGmwcKjSlDiETGpQCAQCLLCLMv2/6dPOAIol9xzVFEgJtFIeS8RF+WFwNjjaL5/DZKiwdXHWm+g0QBHN6vAxOhj6LW8Fzfjb1LXuye6O6PQGUw0rOTDTyMeooI4T8oUDlWP5s6dy6hRo3jhhRcAWLhwIevXr+eHH37gnXfeyTD93r17efjhh3nuuecACAkJ4dlnn+XAgQPF2u6SjN6ckm6YVeYrWItu2cTXnDBlUXDL7vlqMKMoSpGIJHmlILYD/p4u+Hu6EJVg5HJkAo2rFH5359KAPbM6C3Hap5gyX8/fiaechzZfnqRFTUyikbvxBuoEeju6KfnGVnCronc+Ml+Tu2bdz6ftQIr4Wvh+rzZqBXjZxdfO9TMKL87MjbgbTA+dzpLjS7AoFiQknm38LDM6zaCWfy0ATJEXaX9xJurEMOtMbcfCo1NBYz02d+MN/HIgnNXHbnD1fqJ92YE+rvRvXpknmlehXlDJPX8FgvSImFQgEAgEWZE28zXjO61GrbK/P0clCPE111hMqLZNpc2V+dbhSs3gqSU51hsoCejNevr/2p/Td09T2aUrUvQ4dCYLD1Yvx+LhrexFzgVlB4eJr0ajkSNHjjBp0iT7byqViq5du7Jv375M52nXrh0///wzBw8e5KGHHuLKlSts2LCBIUOGZLkeg8GAwZDStTU+Ph4Ak8mEyeQ8XqTFRWyqbr5qRc5yH9gEsiidPsf9ZBM0VShppnVVWR9SFlkhNkGPp2vhnG62deTn+OlNVmFQLeVv/poVPIhKMHL+dgz1A0tmNlxRk5ic6axVKZnuY/fkwmxJlvwdg9xwO1ZPny93U7OCJ+vHtSuSdRSE11YcY/ele6wY+RAtqvk5ujl5JslgID750JX3UOf5OPq5WT/83I3P+f6SGaduxgBQP9CzyM6hGuWtpvcXI+JKzLPiXuI9Ptn3CQsOL8Bgsd7re9fuzfSO02ka2BSwXnPS2bVo1r1GOWM8ipsflr5fo9TtCQpgMhF2L4EhPxwmIt66DHetih4NA+nfPJg2NfztXmclZb/kB5PJhKJYkOWcvxIpisUhMUVp3v/FjYhJBfmhIPGowDkQx7DkU1zHMEmfkjCgWCyYFDnDNP4eVvE1Mi6REH/nS/5wOmLCUa8ehfrWEQBMLUdA1xlW26sSfk3KisyQNUPYeW0n5aVHcYsfj15W6FCnPF8/0wx3Te7O2bzEo5A2Ji2uWFbcP3OPw8TXe/fuYbFYCAwMTPN7YGAg586dy3Se5557jnv37vHII4+gKApms5mXX36Zd999N8v1zJkzh+nTp2f4fdeuXZw5c6ZgG1ECuacH0OCiUti0aWOW0xkTVICKXfsPk3Q5e9+aiLtqQOLUieNobx6z/64ooEKNjMTajf/g61Iom2Bny5YteZ7nyjXrdl25eJ4NiZmfZ9nhorfOv3n/f2hvHc/z/GWB+3HW8+H4of3cP5tx/N0kAA16c/6OYW44FS1hltVciNSx5u8NZOGA4DCOX1UjKxIfrdrPsLoZgzdnJ8YAChpUKOzfuY281qMKi5IANWE377Jhw4Y8zWuR4ewt6zl298JRNoTnbd25Jf6etY2HLtxgw4ZrRbOSQiLJksTau2tZE7mGJNnqUdvIsxGDKw2mgVcDbh65yU1uopKNPHBzBTXubQPgvmcdjoSMJumSDJesx+FOIsw/oybOJFHRTaFbFZmm/mZc1deJPX+dzecdtpnFSnx8PJdvqnDzzDm7V58Qzxb9Zby9izcT+N69e8W6vtKMiEkFBaGoYhlB8SGOYcmnqI+htceXBgmFzVm9Qxut8enW3Qe4d0b4vmZHUMwRmod/h8qSiFHtwbFqo7gjt4R/tjm6aYXCDzd/YO3dtfhYuuNtHIcZaFZepp9/BDu2bs71cvISj0LamLS4YlkRj+aeEmVaGRoaygcffMCCBQto3bo1ly5d4rXXXmPmzJm8//77mc4zadIkJkyYYB++efMmDRs2pEOHDoSEhBRTy52Hc3fi4dg+fDxc6d27U5bTbYw7wYXYCGrUa0TvNtWyXebSGwcgLpaHHmxJt4Zpu+dOPbGd2CQzrdp1sHumFhSTycSWLVvo1q0bWm3e0vU3/3YC7kbQtHHO25UZkfuusXfDefAJonfvZnmevyzw/rHtgJmunTtSK8Azw/j7CUZmHQ/FIEt0ebQrbq6FrMoDEXuvwTmrStSodQfqFNK5VxgoisKbB7cCCidj1LTp2AV/z8LfB0XJ0av34egRKvq48Vifjnmev9L1GL4/fxCL1p3evTvkad5zd+IxH9iHt5uGIQO6FZmdScjtOH68uJ9oswu9enVyCtuU9BjMBr49+i0f7v2Qu4l3AWga2JRZnWbRvWb3tG2Ouoxm1UikeycBMLUeyx5DC7p272W/j56/E8/0pYeJM5moF+jFjy88aC+OVtaIiooibPcVPLz9cpw2MT6Gbu1r4u/vX/QNS8XVq1eLdX2CtIiYVFCQeFTgHIhjWPIprmN4O1YPR3ahUavo3btHptP8HX2MsHN3qVH/AXq3qlpkbSnRmA2ots9AHWatNyAHt8TS9xvuHDxXaq7Dzw98ztrja/E296OcaRQK8FTLysx8vKG991huyUs8Cmlj0uKKZUU8mnscJr5WqFABtVpNREREmt8jIiIICgrKdJ7333+fIUOGMHLkSAAaN25MQkICL730EpMnT0alyujj6erqiqtriudKXJzVK1Cr1ZaKizuvGJOT7DxcNNluf7nkF+4Eo5zjfrIkf9hzd824T71ctcQmmUmyUOj7Oz/H0JS8/e4u+Tv+9YKsPq+X7yWUyfMnN9gKbvl6uma6j/y9UtJQjbKEdxHsx5sxKdWmb8UaaVjZeY5VbJIJU/JFY7Io/H0ygpHtS5avUVSS9RhX9Mn8GOdEoK/VsuN+gjHP85+PtPqPNqzkg4tL0QmDdYP8kCRr1dp4o2L3qXUGzLKZZSeWMW3nNMJjram/dfzrMLPzTJ5q9BQqKd2z8OQf8PdrYNSBR3kY8C2EdETZsMF+Hz19K5YhSw4TnWiiUbAPP49obX8OlEW0Wi2SpEalyjltXpLUDokpxDOo8BAxqaAgiONX8hHHsORT1MdQUlm7VmtUqizXUyG5DkJskkWcT5kRFQYrh8Pt49bhtmNRPToVjSIB50rFdfjrqV95a+tb+Jqfw89s9YR/qUNNJvWqn69EjrzEo5A2Ji2uWLakH7PiJO9VhwoJFxcXWrZsybZtKanlsiyzbds22rZtm+k8iYmJGYJZtdp6MimKSO3PDQmG7CvR2/BJNoDOTcEtm+dr+oJbAN7J3rE6vTlP7SwqClJwC7Bn7167n2hfliAFo1m2G9J7aDP/tuOiUeGavP/jDUVzXqQuEHQtKjGbKYufqIS0RaZ+ORhe4u5fNi/QwHwU2wLsRQj0JtleoC23nLoZC0Cj4KIteOfuoqayn9X39VKkrkjXlVsUReHPM3/S+JvGvLj2RcJjw6nsXZlvH/uW06+cZtADg9IKr6Ykq+j65wir8Fr9YXj5X6jTNc1y/7sRw3PfHSA60UTTKr78MrJNmRZeBWUPEZMKBAKBIDtsBaYzK7ZlwxY73U/IX0HZUs3pNbCog1V4dS8Hz/4GPWbbC72WBkKvhjJs9XDKmV6yC68Te9TLt/AqKH041HZgwoQJDBs2jAcffJCHHnqIzz//nISEBHul2aFDh1K5cmXmzJkDQN++fZk7dy7Nmze3d/F6//336du3rz3gFWSPvRJ9DsWvfNxyL75m9zCyLSe+lIivlXzd8HRRk2C0cO1+QomuVl8UpBbS3LMR+L3dNBh0xiI7L67dT7D/PzzV/52BqOSidxW8XEkymrlyN4EDYVG0qVnewS3LPZFx1m2o6J2/Sq6eLmpcNSoMZpn7OiMe/rl/FJ25Zc0Ue6CyT77WnRdqV/TiRnQSl+7qaO3g47P1ylbe3fYuh24dAsDf3Z9Jj0xiTKsxuGvdM85w94I1uyDyNCBBhzeh4zugTruvj1+P4cWfjhKvN9Oimh9LX3zIft8WCMoSIiYVCAQCQVbYkks02XQbt1k1RScK8dWOSQ//TIZD31uHq7aBJxeDbxXHtquQORlxkv4rnsBb/wpelkcBmNGvEUPbhji2YQKnwqHi66BBg7h79y5Tpkzhzp07NGvWjE2bNtkLHoSHh6fJKnjvvfeQJIn33nuPmzdvEhAQQN++fZk9e7ajNqHEYesSnlPmq29y5mtcrsRX68Mos8xXr+TM13i9c1TBM5it2++SSVtzgyRJ1K7oxYkbsVyK1AnxNR2280urlrIVuL1dNdwrIvHVZJG5EZ1kH06dBesM3NNZA7Iq5dxpUMmHFQfDWXEwvGSJr7bMV5/8ia+SJFHe04VbsXruJxip6u+Rq/lkWeH0reLJfAWoHeBF6Pm7XI50nIB/8OZBJm2bxPaw7QB4aj2Z0HYCb7R9A1+3LPbBiV9h3QQwJYBnADzxHdTqnGGyK3Hw7o9HSDBYaBVSjiUvPIRXDh/mBILSiohJBQKBQJAV5uT3XU0275C2Gg7pe7mVWe5fhpXD4I613gCPvA6dJ4O6dH3kvx57nV4/98Ul/hU85LaoVRKfPtWEAc1Ll8AsKDgOf8saO3YsY8eOzXRcaGhommGNRsPUqVOZOnVqMbSsdJKQR/E1N5mv5uTM18wETbvtQBF1L88rxuS2umrz77hRK1l8vRipo1dhNayUYMt89XDJ/tZiF+WL4Ly4FZNk/zoNEO6ktgPlPV14vnU1VhwMZ+PJO0ztaywxhbci462euvnNfAWr9cCtWD33dYZcz3MtKpEEowVXjSrTYm6FTa1km5FLd4vfduB05Gne2/Eea86tAcBF7cLoB0fzbvt3qehZMfOZjAmwYSIcX24drtHBKrx6Z/SsPBAWxTdn1RhlC21q+vPD8FY5XrcCQWlHxKQCgUAgyAyznNzTM5vM13JCfE0hs3oD6WyvSgMx+hh6LhuA6f4oPORmuKglvn6uBd0bZe4XLyjbiDetMkZistjlmcNLdp48X22Zr5qMDyOb+BrnZLYDrvnMfIUU31dn8YF0JnKbWe3tasuILvzzwpbp6u2mIV5v5kZ0IhZZyXN1yaLCFpD5e7rwQGVfGlf25eTNWFYdvVFiCm/ZbQfymfkKKdkB93W5D1BtWa/1K/lkm3lQWNiu9cvFeK1fjbnKtNBpLPtvGbIio5JUDGs6jKkdp1Ldr3rWM0aetdoM3D0HkspqMdDhTcjEZH/PpXuMXHYUoyzRrpY/i4c9lK1NiEAgEAgEAkFZxm47kI3na3khvlrrDWx8G47+aB2u/ggM/B58Kjm2XUWA3qznsWVDib75Iu5Kddy1KhYPa0W72hUc3TSBk+KwglsCx2ATx3J60c6b7YDtS2Bmma82z1fnsB0oqOcrWLsigxBfMyO3Bd287IXYCv+8sPm9tgrxx0WtwmRRuBWTlMNcxce95ExPW9GpZx+qBpSswlspBbcKkvma96IEp24m+70GF73fK6Rc6zdjkvJcGCyvROgieHXjq9T9qi4/nvgRWZF5osETnBp9ih/6/ZC18KoocHQZfNvZKrx6BcHQtdDp7UyF19Dzkby49BB6k0wDP5lvn28uhFeBQCAQCASCbLDZDmgzed+1Uc4jRXwtKTF9oXL3PHzXJVl4laDDWzD0r1IpvMqKzMCfJ3Dt8tO4KNXx91Tx+//aCeFVkC1CfC1j5Lbgll18zUVmoikb2wGbf6DOSTJfDYUgvtp8Xq/c0yHLZfDBmg1JptzZDni7FV3m67XkzNeaFTyp4m8tRORM1gOpbQcAHm8WjKeL2l54y9kxmC1EJ1pF84rebvleToVk8TkvtgPF6fcK1u5jtgzdK3eLxvc1Vh/L+9vfp9aXtfjq4FeYZBNda3bl4MiD/Pn0nzQIaJD1zAYdrHoJ1o4FcxLU6gIv/ws12mc6+bazEbz00xEMZpku9QIYWU/GVSuEV4FAIBAIBILssNkOZNeTzpZYYDDL9oSnMsPxFfBtJ4g8A54VYchq6DI5Q6HX0sKzP3/EyXOPoqYcVfwl1o3rROMqxfN+Iii5CPG1jJFbz1efVF6tNk/XrDBnYzvgU4QiW36w2w5o8i84VC3njotahd4kc9OJMiqdgdxmvtptB4rA89WW+Vq9gifVkws5XXOiolupbQfA+oHi8WaVAVhxMNxh7cotNssBjaTg657/gMpuO5DLzFdFUTh9KznztXLxZL5CSvbr5UL2fU0yJfHJnk+o+WVNZu2eRYIpgVbBrdg6ZCtbhmyhVeVWaaa/HpXIpFUnmbvlAhtO3ub62QMoizrCyd9BUsOjU+D5P8ErINP1bT59h5d/PoLRItOzURBfPdOUAnyDEggEAoFAICgz5KbglrtWjWtycFVmrAeMCbDmFVjzMpgSoUZHayJAJoVeSwOKovD8T0s4cLoJKtyoG2xi02vdCfZzd3TTBCWA0vkpQpAlScnia249X8Ga/ZpVISBFUexFrLSZFtxKth0wlB7bAY1aRY0KnpyPiOdiZHyuK7WXBZJy6/lahKK8zfM1pLwH1ct7Ane5FuW4avXpuZfscWr7Og7w3EMphbem9TXaDfudEVuxLV8XkKT8++iWz6P4eidOT1SCEbVKom5y9nlxUKuiFwevRhWazYjJYuKHYz8wY9cMbsXfAqBBhQbM7jKb/vX7Z7pPTRaZMb8c5b8bsYDCc+rtPKr5CUkycU8qz4rq03CRH6bexXvUD/Ih0Mc1zXLW/3eb1349hllW6NOkEp8PagZyGcvIEAgEAoFAIMgnuSm4JUkS5T1duBVrjVlL/TtixBlrvYF75631BjpNgvZvZGp7VRowWWSeX/IXBy9ZC982Doli9ajni6UOhaB0IMTXMkZCcqZhTh5/WrUKTxc1CUYLcUmmLMXX1FXlM/PAcTrbAUvBxVewFuI5HxHPpUgdXeoHFkbTSgU2WwuPHGwtUryAC/e8sMgK4Xbx1ZNqyUFPuFNlviZ7vnqm+KU2ruLLA5V9OHUzjj+dvPBWRHLmq08B9eG82g7Y/F7rVPTCrRi7ytcK8AQK7vEsKzK/nfqNKaFTuBR1CYBqvtWY3mk6Q5oMQZ1NoLpgx2X+uxFLsJuJBT4/0ixuOwDbLc14w/Qy0ed84Nw5+/S+7lrqBXpTL8gbH3cNC3dewSIr9G8WzKdPNUWjVmES4qtAIBAIBAJBrkjJfM0+8cDfK0V8LbUoChxbBhvestpeeQXBk4sh5BFHt6zIiNObePb7rZy+4YKCTONaF/hrxOuosvEAFgjSI8TXMobNf8bTNWfxwsddS4LRQmw2RbdMqSwJMrMdKMoMx7yiKEpK5msBv1DZqqCLoltpsdta5CCOeRWR7cCdOD1Gi4xWLVHJ143q5Z3LdkBRlBTbAa+06uVzD1Xn3dUn+eVgOCMeqVGgrNKiJCLOlvlaML9ju+2ALnfBaXH7vdqwXev5tR1QFIWNlzYyeftkjt85DkCARwDvdXiP/7X8H66a7IuWnbwRy1fbL9JICuM3z4V4xV0HlQa5y1Rq1nuBDyMTOH8n3voXEU/YvQRik0wcvBrFwaspHsJPtqzCRwObZOtVJhAIBAKBQCDIiC3hKLvMV0hbdKtUYoiHdROstlcAtR6FAYuytL0qDVyPSuS57//lepSMjJ66tfbw14hPhPAqyDNCfC1jJBhzVxAJrNlTt2P1OYivqTJfs7EdyE3hrqLGmEoodtUK8bUoyKvtQGFnRF+7Z7UXqFLOA41aZRdfw6MSURTF4YJmnN5sv2bKp8smf7xZMLPWn+HK3QQOhkXRumZ5RzQxR2yZr77aHCbMAZvtgq0ibE7Hxpb52ii4+PxeIeVaD7uXgNki56lr0b/h/zJp2yT+Df8XAB9XH95s+ybj24zH2zVn6wS9ycLrvx3jOWkT77v+gjbBBL5V4cklqKq2IgQICfCmR6OgNPNcvqvjQkQ85+7EczFCR8NKPkzoVheVEF4FAoFAIBAI8kyK+Jp9HGiL70ul+HrnpNVm4P4la72BLu/Bw+OhFIuQx8KjeXHpQaITzZi5T5Xqf7PuhWXZ9lgTCLJCiK9ljNyKY5Di+xqnz13ma2ZfAlMyXx3v+WrLeoXCy3y9GKlzClHPWUjIte1A0WRE2/xebaJrlXIeSJK1cFxUgpHyXtlnGRY1tkDM00Wdoeu8l6uGfs2CWXHwOr8cDHda8TWykDJfbbYLRotMvMGMj1v2au6Z5MzXByoXb+ZrsK877lo1SSYL4VGJ1EwuwJUdJ+6cYPL2yay/uB4AN40bY1uN5Z1H3qG8R+6P61frD/NGzCx6aQ+BAtTrA/2+Bg//LOdx06ppFOxb7BnCAoFAIBAIBKUVWwHqnGwHyuWxpkGJQFHg8A+waRJYDOBTGQYuhuptHd2yImXDydu8/ttxDGYZo3QF30or2Dh8PW4aN0c3TVBCKb2fKQSZktfMVyBXtgNatZSpAGkT2QxmOY346QgKU3ytUcETlWQVD+/G586zsiyQlEvbAe8ish24dt+a+RpS3urT6aZVE+RjfUBei3K89YDN7zW95YCN5x6qDsDGk3eIdtKgLSJVwa2C4O6itn8EisrBeiAqwcitWOt6G1QqvmJbACqVRM1k39fLd7Mv3HYp6hLP/fkczRc1Z/3F9aglNaNajOLiuIt80v2TPAmvJw9u55ljz9NLfQhZpYWeH8Izy7MVXgUCgUAgEAgEhU9ubQdsma/OGsfnGX0c/PECrJ9gFV7r9oSX/y3VwquiKHwTeplXlh/FYJZJVB1EKj+PzcN+pZx7OUc3T1CCEeJrGSPRkAfPV7dciK9m64MoM8sBSPH2BGv2oSMxphKKC9r91k2rtlewFNYDKdg9Xx2U+XotXeZr6v/bhFlHci9ZZPT3zDwD11Z4y2iR+fPojeJsWq6x2w4UUHyFFOuB+wnZf8Cw+b3WqOBptzIpTnKyGbkVf4vR60bTYH4DVpxagYLCoEaDODPmDN/2/ZYqPlVyvzJFQb/rS+pveIqq0l3uayuhGrEZ2owGkWEvEAgEAoFAUOykFNzKXj4pVZmvt47Bog5wejWoNNB9Fjz7a6lOBDBZZCatOslHm6yFbOPUazF4f8nGIWuo5lvNwa0TlHSE+FrGSLRnJhZS5qtsEzQzP5U0ahXuyVmQjrYeMJisbXXVFI5HSx2bIJPPQjz/Z++8w6OoGi7+25beAwkJvVgIXVSkCtLxVUDkE0XBBhawAPoqUkQsKApiR18bKFYUUKRI70VReu8tCaTX7fP9MTubhJJsmc2m3N/z8OhuZmfv7k42d86ce05VpNDprHYt8zXfbMVu9275enFOXuJ8BagfI/9/RSjdUmIHaoReXbm892b5D/t3208jSeq9N2qhFG5FeBk7AEUidFoZztd95+W816RyzntVaFzzyqVbGYUZvLDiBZq834TZO2ZjtVvp06QP/4z8hx/u/oFrY69174kKMuD7ewlaPQkDVtZo2xM4ehPUbqvWSxEIBAKBQCAQuInVcc7rsvO1oBKLr5IE2z6FL3pB5gmIrAcPLYMOT1VpI8C5rEKGfLaVH/46A0hkGD4lL+grFgz5hZbxLf09PEEVQIiv1QibXaLQojgTyxYgFfE1p/Dq7sSi2IGrH0q+cjm6i+J8DdCrc9g3VnJfU4X4qpBvcrFwy+GMlaSiKAxvkSTpis7XekrpVgUSX2NKEV/vbJVISIDOWbxVkSgwW52/x2o4X2u4WEqw95wj79VPOaaXOl/zzfm8seENGr3XiOmbp1NoLaRD3Q6se3AdS4cupU1CG/ef5PQ2mN0ZDi/FJOmZZHmIkKHfEhZZMbN/BQKBQCAQCKoLrjpfFWNBpS3cKsyEH++Hpf8Fmxmu/w88vh7q3uTvkfmUlftTuf39Dew4lUmA3saFgKnk6n9nzoA53NbwNn8PT1BFEIVb1QhFeAUIdSHzNSJY3ibHpdiBq18FCw/ScyHX5H/x1ZH56m3eq8I1cXL25G6HMCSAAkXcL+P4CjTo0GkkbJKGXKNVlaXkF3NNFFpsaDVy0ZaCM3agAmS+puWVnvkKEB5kcBZvfV/BireUyIHQAB1BOu9/n52xA3mlxw7sdzhfm/nZ+Xr0Qh4fbPuQ1ze8Rmp+KgAt4lrwRvc3uP2a2z0r3rPbYfP7sGoqSDZOU4snzE/ToVM32jWuoebLEAgEAoFAIBB4gOJ8NZThfI0Jlc9pKqX4enYHzH8Qsk6D1iDHDLR7rEq7Xc1WO9OXHeTzjScAqBNjY1v+SKzaVN7u+Tb3trjXzyMUVCWE87UaUeBwGGo0EGQo+6N3JXbA7ILzNcwhrPk9dsCqrvO18zU10Gs17DqT5RSHqjsFjlzf0DKcrwDBjk3UEuVPOpyttaODS3zGFTN24MqZrwpK9MCSvRWreEuJHIgLL338ruJK7ECeycrxNDlOwl/ia92YIDQaiTyTlTFLJ5Oan0qj6EZ8O/Bbdj6+k/9c+x/PhNf8NPju/2DlyyDZ+CusG/2Mr2Gu2Zxxva5T/4UIBAKBQCAQCNxGKdzSlSm+ynPb7EKLc4VohUeSYPOH8GUvWXiNbgCP/Am3PF6lhdczGQUM/nSLU3jt1ULPX6Z7sWpTefrmpxnXfpyfRyioagjxtRqhlG2FGHQuCQXO2IFSRFNrsRKrqxHhiB3wd+GWySq/frXE1/iIIHo3rwXAnM0nVdlnZUfJFA52QXx1HBaqifJK3qsitioosQNpeSby/XwMuhI7ANCidiTNEiMwWytW8ZZTfI1QR3ytEVZ27MCBZPnCRkJkELFh6jyvq0iSxKKDi7j58zaYOQ9AXGArPu73MQdGHWBoy6FoNR5+n5zaDLM7wdEVoA9iZ+tXGJz2KEZtKO/e05oggzrZ1AKBQCAQCAQC73A1diAy2ODUKytF7qujb4A/J4DdCkn94bH1UPsGf4/Mpyzbm0y/9zew60wWkcEGJt5Zgx/P/B9mewF3J93NzN4zPTNWCASlIMTXaoSSrVlWE71ChCuFWzYldqASZL5alcIt9Q77Bzs0AGDhznMVyqHoLxR3dagLx5jaztdTivhaLO8V5ElQVIh8LJ/2c/RAusPhWVrsAIBGo+G+drL79fsKVLx1wRE7oJbz1Rk7kH/12AEl77W8Xa9rT66lw5cdGPDjAPZd3Ad6OWZgaudPeeKmJwjQeRh6a7fD+rfh69shNxliryFtyBKG7WwKaHi6+zU0r+2fbFuBQCAQCAQCweUozteyCrd0Wg3RIY7SrXz/rvosk2J9A+gC4fYZMHgOBFXdeajRYuPlRXt5/Nt/yDVauaFeFJ8/1JgpWweRY8qhc73OfDPwG3RaYYIQqI8QX6sRhQ5XoitLwsG12AFXCrfCAhXx1b9/gMwqxw4A3Fg/mqSECExWOz/9fUa1/VZWnM5XF1x7QTp5ElOas9odlFiBBrGhl/2sfkxIiW38hSIylhU7AEXFW8cqUPGWr2IH0kuJHdjnzHstn4ngjvM76P1tb7rN6cbWs1sJMYTwUqeXGHHzHQCcSffiIkveBfj2Llj9Gkh2aDkEaeQaxqyzkmO00qpOJE92bazSKxEIBAKBQCAQqIGy2lNfympPhWiH6aM0c4Ffsdth47vwVV/IOQsxjeHRlXDTo1U6ZuBkWj6DPtnMnC2nAHjs1kbMHnY9Dy3uz7nccyTVTGLRkEUE6YP8PFJBVUWIr9WIfOeScNecr87YgULLVZ13ZhdiB5QypVw/L/lWxqpW4RbIDsXhHeoD8M3WU9jsFcOh6A9sdsmZq+uK8zVIdeerLKxe6nwFqOcQZE9n5KvyXJ4gSVJR7EAZzleQf2/ubJUIyO7XikBqrjyJjI9QZ1ISG6o4X10RX33rfD2YdpDBPw/mxv/dyJ/H/sSgNTDqplEce/oYr3d/nWYJcvHZ0Yt5nj3B8XVyzMDxNaAPhv4fw12f8u2/GWw4kkagXsuM/2td5nI2gUAgEAgEAkH54qrzFSDWYS6okM5XZ9/AFJBs0PxueGwdJLT098h8ym+7zvOfDzay73wOMaEBfPXQTYzp2ZDB8+9i38V9JIYnsnToUqKDo/09VEEVRpzlVSPcKUOCIvHVLl09r9VaiWIHTBb1na8A/VvXJirEwNnMQlYdSFV135UJJXIAIMSVwi1n5qv3x4UkSc7M1wY1KqbzNddkdcZ0xJaR+aqgRA9UlOIttZ2vscUyX+1XuHBhsto4kpoL4LOl+Geyz/Dob4/S7ONmzN8/Hw0a7m95PwdHH+TDfh9SK0zOdW4cFwbA0Qtuiq92G6yZBnP7Q14q1GwKI9dCm6GcTMvnjT8OAPBCn+tp4ngOgUAgEAgEAkHFwdXMVyjqdsioaM7Xk5tK9A1wx/sw6HMIDPf3yHyG0WJj/K97ePr7f8kzWbm5QQxLnu7MrdfWYNiCYaw/tZ6IwAiWDl1Kvch6/h6uoIojxNdqhOJ8dTXzNVCvdbpErxY9oMQOlCZoFsUOVAzna6Be3QyXIIOOe26qC8BcxzKG6ogSa6HVuJarW+R89f6qcGaBxXl81Yu5kvNVvs+fma/K0vrQAJ3LZUoVrXjrguqxA/Lk1GaXrhg/cTglD6tdIjrEQEKkukuALuZfZOzysVzzwTV88e8X2CU7d153J7se38U3A7+hUXSjEtsrwmhqjsn1YzY3RRZd170JSNDmfhixGuKux2aXGPvTTgotNto3inXmRwsEAoFAIBAIKhZWu2O1pwvO12gXVnaVK3YbrHsb5vxH7huoca08H207vErHDBy9kMeAjzbx/fbTaDTw1G1N+G5EO2pFBjFu+Th+3v8zBq2BBfcsoGV81Xb+CioGQnytRhQqhVsuCj8ajabM0i1F0CxtCUaEI3Ygr4JkvqpZuKVwf7v6aDWw8WgaRy/kqr7/yoBT3A/Qu9QOqWbhluJ6TYgMuqKwWRGcr8rVb1ciBxQ0Gg333lwxirckSSI1R4kdUEd8DdTrnM74tCvkvu49L5dtNa8dqVrjaI4phylrp9Do/Ua8u/VdTDYTt9a/lc0Pb2bRkEW0iG9xxcdFBBmcovOxiy7EVxxdBZ90hJMbwBAKAz+D/h9BgHwsfrr+GP+cziIsUM/bg1uidWEyLxAIBAKBQCAof5TYAZ227PNIZYVbRVi15uwbWOPoG2h1n7wCK76Zv0fmUzYfTePODzdyMCWXGmEBzH34Zsb1ug69TsvMLTOZtW0WAF8P+JrbGt7m38FWQ9avX88dd9xBYmIiGo2GhQsXOn9msVh44YUXaNGiBaGhoSQmJjJs2DDOnz9fYh8ZGRkMHTqUiIgIoqKieOSRR8jLK7lCcffu3XTu3JmgoCDq1q3L9OnTy+PlXRUhvlYjipyvrjs/Ix1rw3MKryyQuVK4VVFiB3xRuKVQNyaE7k3jAZizuXq6X5XYAVciBwCC9PIkRg3n6ymH+Hol1ysURRGcyyp0HrPljeJ8jXGhbKs4/VsXFW/9dTLTF0NziVyTlUKL/B2ilvMViuW+5l2+NGufQ3xNUiHv1Wg18u6Wd2n8fmNeWfcKeeY8bki4gWVDl7Fm+Bra121f5j4a15Tdr8dKix6wWWHVVPh2EBSkQXxzOUur1T3OTfafz+HdFYcBePmOJOpEX/m4FQgEAoFAIBD4H7cKtyqK89XZN7AWDCEw4BMY+AkEXB7RVpUoNNt4fv5uCszy6rIlT3em8zU1Afhh7w+M+3McANN7TOe+Fvf5c6jVlvz8fFq1asVHH3102c8KCgr4559/mDRpEv/88w+//vorhw4d4s477yyx3dChQ9m3bx8rVqxg8eLFrF+/npEjRzp/npOTQ69evahfvz47duzg7bffZsqUKXz22Wc+f31Xw7X154IqQVHmq+sfe1nOV2fma2mxAxVEfDVZZeFIzcKt4jzYoQEr9qfyyz9neb7PdU7Hb3WhwOl8dU18VdX5miY7WhvEXnkyERceSJBBi9Fi51xm4RVzYX2NMgGr4WLeq4JSvPXDX2f4btspbm4Y44vhlYkSORAZbHA5NsEVYsMCOZle4CwjK87ec0rZlud5r1a7lTk75/DKulc4k3MGgGtjr+W1bq8xKGkQWo3r3wdN4sLYcjz96qVb2efgl0fh9Gb5dtuHoM80MAQ7NzFZbYz9aScWm0TPpHjublvH49cmEAgEAoFAIPA97hVuOZyvBX4SX+02WPcWrJsOSHLfwOCvIe56/4ynnPlwzRHOZRVSOyqYLx68kRCH9rHmxBqGLRgGwNM3P81zHZ7z5zCrNX379qVv375X/FlkZCQrVqwocd+HH37IzTffzOnTp6lXrx4HDhxg2bJl/PXXX9x4440AfPDBB/Tr14933nmHxMRE5s2bh9ls5ssvvyQgIIBmzZqxc+dOZs6cWUKkLU+E87Ua4a44BkWlWzllZb6W6nx1xA5cpbSrvHDGDhh8c9h3aBxLk7gwCsw2ftnh/3zO8qagWOyAKwSpWLilOF/r17iyg1Cj0Thdsaf8lPuqiIsxboqvgDN6wJ/FWynZ6kYOKCgT1LRLXpfVZudgiiy+NvfA+SpJEvP3z6f5x8159PdHOZNzhjoRdfj8js/Z9+Q+Bjcb7JbwCkW5r1cs3Tr8p+wuOL0ZAsLh7i/hjlklhFeAWSuPcDAll5jQAKbd1UK1OAWBQCAQCAQCgW9wp3DL6Xy9QqSWz8lJdvQNvAVIcMMwZ99AdeDohVw+W38ckFeXKeele1L3MODHAVjsFu5OupuZvWeKObjK5ObmkpOT4/xnMqlXOJednY1GoyEqKgqALVu2EBUV5RReAXr06IFWq2Xbtm3Obbp06UJAQNG5d+/evTl06BCZmf5ZTSrE12pEvpviGBQTX6+yNNyVzFclduBq+ygvTC4Ixd6g0WgY3r4+IBdvXam9vSqjOKvddb6qcVwogurVnK8A9WLkn51OdyGv0wc4YwfcyHxVaFknkqQEuXjr13/PqT00l0h1OF/jI9Qtvop1vB8Zl0xQj6flY7TYCQ3Qlfq5XookSfx57E9u+t9NDP55MIfSDxEbHMuMXjM48tQRHrnhEfRazxZ9OGMHijtfbRb4cxJ8NxgKMyChlRwz0HzQZY/fcSqDT9cdA+CNgS2oEaaukC0QlMa0adO46aabCA8PJy4ujgEDBnDo0KES23Tt2hWNRlPi3+OPP15im9OnT3P77bcTEhJCXFwczz//PFZryYtoa9eu5YYbbiAwMJAmTZrw9ddf+/rlCQQCgUDgM5TCrQrtfD26SjYCnNwAAWFw1+dw5wfOvoGqjiRJTFq4D4tNovv1cfRMkiMBz2Sfoe+8vuSYcuhcrzPfDPwGnVbdAm4BJCUlERkZ6fw3bdo0VfZrNBp54YUXuPfee4mIkA05KSkpxMXFldhOr9cTExNDSkqKc5v4+PgS2yi3lW3KGyG+ViOUTM5QNzJflaXzV4sdsFjLjh1QxNc8k9WvgqQvM18V7rqhDuGBek6k5bP+yEWfPU9FRHG+Brua+apTMl/VcL7K4mv92KtPLpSf+at0K91RuBXrgfNVo9FwXzvZ/frdtlN+Kd5KzZXF17hwlcVXRwau8v4oFM97dbWMauvZrXSf253e3/ZmR/IOwgLCePnWlzn+zHHGth9LkN67sSvO11PpBfL3SdYZ+KofbH5f3uDmx+CRFRDb+LLH5pusjP1pF3YJ7mpTmz7Na3k1FoHAXdatW8eoUaPYunUrK1aswGKx0KtXL/LzS16QGjFiBMnJyc5/xcsJbDYbt99+O2azmc2bNzNnzhy+/vprJk+e7NzmxIkT3H777XTr1o2dO3fy7LPP8uijj7J8+fJye60CgUAgEKhJkfO17DmpssotI99cPnN2mxVWviIXaxWkQXwLGLkOWg72/XNXIH7bdZ4tx9MJ1GuZcmczNBoNmYWZ9J3Xl3O550iqmcSiIYu8Ph8QXJn9+/eTnZ3t/Dd+/Hiv92mxWPi///s/JEnik08+UWGU/kVkvlYj3F0WDkXO16tmvtpdiB0IlPchSVBgsREW6J/DrjzE19BAPXffWIevNp1k7pZTdL0uruwHVRGc4r6Lx1ewM3bAO+drdqHFuaS/fikOSaf46ufYgVg3C7cU+rdO5PU/DjiLt8o7+/VCjm9iB2KusjRrnxt5r3sv7GXi6oksOrQIgABdAKNuGsX4TuOpGVpTtbHGRwQSFqgnz2Ql7e8FJK4dC8YsCIyE/h9C0p1Xfey0pQc4lV5AQmQQL99ZtRtmBeWLssxLITAwkMDAy39Ply1bVuL2119/TVxcHDt27KBLly7O+0NCQqhV68oXB/7880/279/PypUriY+Pp3Xr1rz66qu88MILTJkyhYCAAGbPnk3Dhg2ZMWMGAE2bNmXjxo28++679O7dW42XLBAIBAJBuaJkvhq0ZZ9HKnNbi00i12T1bQ9I9jn45RE4vUW+fePD0HsaGKqXwJhjtPDq4gMAPHVbE+rGhGC0Ghnw4wD2XdxHYngiS4cuJTo42s8jrbqEh4c7nalqoAivp06dYvXq1SX2XatWLS5cuFBie6vVSkZGhnMOW6tWLVJTU0tso9y+2jzX1wjnazXC3TZ6KDvzVYkdMJRyFTDIoHUu0VCj2d5TTErmq963ywweuEWOHlhz6IIzi7Q64G6mcJBjszyT1aurwqcdTtYaYYGlCvtK5utpfzlfvYgdgKLiLYAFfoge8HXswKXO170O52uzUvJeT2adZPjC4bT8pCWLDi1Cq9HycOuHOfLUEWb2nqmq8AqyA/m6GgFM0n9D4rKHZeE18QZ4fH2pwuuyvSl8u/U0AG/f3cr5vSoQqIGny7yys+XfsZiYkhdy5s2bR40aNWjevDnjx4+noKDoO3PLli20aNGixDKu3r17k5OTw759+5zb9OjRo8Q+e/fuzZYtWzx6fQKBQCAQ+BtFfNW5sBoryKBzng/5tKvB2TewxdE38BX8591qJ7wCzPzzMGl5JhrVDGVEl0bYJTvDFgxj/an1RARGsHToUupF1vP3MAUuogivR44cYeXKlcTGxpb4efv27cnKymLHjh3O+1avXo3dbqddu3bObdavX4/FUqQ/rVixguuuu47oaP+I8ML5Wo3IN7lfuBXhsCeWFTtQWvi4RqMhPEhPZoGFXKOVBM+Ly72iPJyvAI1qhnHrtTVZd/gic7ecYtJ/knz6fBUFZ6awi7EWSuarXZIf66kj+qRD4G5QSuQAFLliT2cUIElSuYesexM7oHBL4xh+/PsMJ9PKX9QvEl/Vdb4quafFna+SJLHv/NWdr6l5qby2/jU+3fEpFrv83XR30t282u1Vrq/hw0KBzJO8m/8i9fQH5du3jIIeU0B/9c/0913nGfPjTgCGt69Pp2tq+G58gmrJ/v37qV27tvP2lVyvl2K323n22Wfp2LEjzZs3d95/3333Ub9+fRITE9m9ezcvvPAChw4d4tdffwVcy8+62jY5OTkUFhYSHFyyhE4gEAgEgoqOVek5cSF2ACA6JIACcyHp+eZSV+Z5hM0Cq6YWxV4ltILBX0NMI3Wfp5Kw91w2c7ecBODV/s0J0GkZs3wMP+//GYPWwIJ7FtAyvqV/BykoQV5eHkePHnXePnHiBDt37iQmJoaEhATuvvtu/vnnHxYvXozNZnPOMWNiYggICKBp06b06dOHESNGMHv2bCwWC6NHj2bIkCEkJspmpfvuu49XXnmFRx55hBdeeIG9e/fy3nvv8e677/rlNYMQX6sVhQ5xLNQNkaus2AGL0/lauqAZVkx89RflJb4CPNihAesOX+Snv88wrte1bkU9VFYKnc5q116rQSuH1lvtEnlGq8fiq+IurleG+Fo7KhitBgotNi7mmohT2cFZGpIkFcUOeFGylBApixbJ2YWqjMsdUh2xA2q/b87YgWLOgDMZheQarQTotFwTH+a8P8uYxdub3mbWtlkUWGQ3Xs9GPXmj+xvcmHgjPmX/Ilj0FPVM2WRJofxc5yVG9Bld6kO+336alxbsQZLk2IiJ1eRCjKB88WSZ16hRo9i7dy8bN24scf/IkSOd/9+iRQsSEhLo3r07x44do3Hjy7OMBQKBQCCoDjgzX12IHQB5Zde5rEL1na9Zp2H+w3D2L/n2zY9Br1dBXz1LXO12iQkL92KX4M5WiXRsUoMZm2fw3rb3APh6wNfc1vA2P49ScCl///033bp1c94eO3YsAMOHD2fKlCn89ttvALRu3brE49asWUPXrl0BeaXW6NGj6d69O1qtlkGDBvH+++87t42MjOTPP/9k1KhRtG3blho1ajB58uQSc93ypuorQgIn+Q5xzNVCJIAIlzNfS78KKOe+Fvo1dkCJSAgsQyhWg1uvrUn92BBOpRew4N9zDG1X3+fP6W/y3Ywd0Ggo5oi2UCvSM1HvpCNGoEEZV5UD9FoSo4I5m1nIqYyCchVfc01WLI5JmzfO10Sn+GosV/euJElcyPVt7EBmgRmbXUKn1TjLtq6rFY5Bp6XAUsCH2z/kzY1vkmnMBKBd7XZM6z6Nbg27XXXfqmAxwp8T4a//yeOMbcPt5x4i1tiYEaU87H/rj/P6Ejl76r529Xitf3OXi8MEAl8yevRoFi9ezPr166lTp06p2ypLt44ePUrjxo2pVasW27dvL7HNpflZV8vYioiIEK5XgUAgEFRKlHNeV52vVzIXeM3BP2Dhk3LsVVAk9P8Imt6h3v4rId//dZpdZ7IIC9Qz8fam/LD3B55b8RwA03tM574W9/l5hIIr0bVr11JjB12JJIyJieG7774rdZuWLVuyYcMGt8fnK0TmazVCyeR0tRAJimW+XsWxanbEDpTlfA0Pkp/Tn85Xk1V+/eXhfNVqNc7s1zmbT/qlnb68KXRTfAWcbterHV+uoGS41i/D+Vp8m1PlnPua4VhSHxKgI8jgeeZwfKR8VdtktTudtOVBZoHFKR7HhatcuBUiT04lSRZgoSjvtWlCGLP/nk2T95vwwsoXyDRmklQziQX3LGDLI1t8L7ymH4MvejqFVzo+Q8bgBZynBscu5mG3X/57LUkSM1ccdgqvj93aiNcHCOFV4H8kSWL06NEsWLCA1atX07BhwzIfs3PnTgASEhIAOT9rz549JUoOVqxYQUREBElJSc5tVq1aVWI/K1asoH379iq9EoFAIBAIyhcl81Xv4nxOmd+q4ny1mmHpi/DDfbLwWrstPLah2guvaXkmpi87BMC4XteyL30LwxYMA+Dpm5/muQ7P+XN4AsFlCPG1GpFvcr9wS2lnLCt2oLTMV6gY4qvZWbhVPof94BvrEmzQcTg1jy3H08vlOf1J0fHlurhfdFx47oguynwtO0+pXowj97Wci9Ccea8elm0pBOp1zozU5Gyj1+NyFSXvtUZYQJkXWtxFr9MSFSJ/zyi5r3vPyXmv84+8yxN/PEFyXjL1I+szZ8Acdj++mwHXD/C963fPfPj0VkjZDcExcN/P0HMq9WpGotdqKDDbSM4p+RnY7RJTF+/n/VVHAHi+93W82Of6cs8XFgiuxKhRo/j222/57rvvCA8PJyUlhZSUFAoL5RiTY8eO8eqrr7Jjxw5OnjzJb7/9xrBhw+jSpQstW8pZab169SIpKYkHHniAXbt2sXz5ciZOnMioUaOcWbOPP/44x48f57///S8HDx7k448/5qeffmLMmDF+e+0CgUAgEHiDM3bAxXmw4nz12iyRcQK+7AXbPpFvtx8NDy2D6Kq/qrIs3lx6kOxCC0kJEbRplMuAHwdgsVsY1HQQM3vPFPNvQYVDiK/VBJtdwuQQH90RXyMdoojZasdosV32c5djBxwibp7Jj7ED5Zj5CrJr+K4b5BKUuZtPlctz+pNCi/vOV29F+QKzlQu5srDpiviqlHKdLGfnqyIqxoR67xpNjJKX/Z/PKr/cV0V8jQv3TVSDEsWQnmfij8N/sP7ocQDOGbcRFxrH+33e59DoQwxrNQyd1nPnsEtYCuH3Z+CXR8CcC/U6wOMb4dpegOzyb1BDPtaOXchzPsxml3jhl918tekkAK/c2YxR3ZqIiZ+gwvDJJ5+QnZ1N165dSUhIcP778ccfAQgICGDlypX06tWL66+/nnHjxjFo0CB+//135z50Oh2LFy9Gp9PRvn177r//foYNG8bUqVOd2zRs2JA//viDFStW0KpVK2bMmMHnn39O7969y/01CwQCgUCgBso5r8FF52u0GrED+xbCp13g/L8QHA33/gC9Xy+16LW6sP1EBvN3nAXg6Z41+c/3/cgx5dC5Xme+vetb358vCAQeIDJfqwkF5iJxy53CrbAAPVqN3EifU2i5bMl05YodKF/xFWBY+wbM23aaP/encC6rkNpRVTfvzhPnqxI74OlxocQHRIUYnBcKSsMZO5BRzrEDStmWF3mvCgmRQew+m+0X52t8hG/C/GNDAzl2MZ+n/hjPrsxfqGP/Bgk7L3UdxriOTxMWEFb2TtQg7Qj8/CCk7gU00HkcdB0PupLHdJOaYRy9kMfRC3l0ubYmZqudMT/u5I89yWg1MP3uVtzdtvQsTYGgvCkr/qZu3bqsW7euzP3Ur1+fJUuWlLpN165d+ffff90an0AgEAgEFRUldkDnoviqzPk9ih2wGOHPCfDX5/Ltuu1g0BcQVdf9fVVBLDY7kxbuBeCuG+J5bu3dnMs9R1LNJBYNWUSQvvx6PQQCdxDO12qCkveq1bi37F6r1Thdq1eKHlBiB8oSX70V2dTA6Xwth8IthetqhdO+USx2Cb7dWrXdrwUeZL6GB3oXO3DKER9Q3wXXK/gzdkBN8VUW8M9nl6fzVXYXq122BbAzZScHM+XG1iNpKYRqmgLQuGYoL3d7qfyE110/yjEDqXshtCY88Ct0n3SZ8ArQOM7hfL2YR6HZxshv/uaPPckYdBo+HnqDEF4FAoFAIBAIqhDuxg547Hx19g04hNeOz8KDfwjhtRhfbzrJodRcokIMbM+dwL6L+0gMT2Tp0KVEB0f7e3gCwVUR4ms1oXjZlrvLYJXSrdLE17KaHxUBtyI4XwO9KDzyhOEdGgDww/bTV4xuqCoosQOhgeUXO6DEBzRwoWwLoJ5ju8wCCzle5My6izN2wMvMVyiKHUjOKn/na5yK4uuR9CPc+8u9tPm0DefyDgJwY3w3/nvT+wC0qhOj2nOVirkAFo6CBSPBkg8NOssxA41vu+pDmsTJgvCec9kM/3I7aw9dJMig5YvhN9GneUL5jFsgEAgEAoFAUC5YlXNed52vBW6Ir3vmyzEDKbshJBaG/gI9XwFd2av7qgvJ2YW8u/IwANE117Lp7J9EBEawdOhS6kXW8/PoBILSEbED1QRlSXiwG65EBUV8vZJYpVwFLMtNqkaxkreYbeXvfAXo0TSO2lHBnMsq5Pdd5xl8Y9W8cplvksXXYIMbsQNeHhdO52uMa+JrWKCeGmEBpOWZOZ1eQPPakR49r7tkKIVbKjpfk/3ifPU+duBczjmmrpvKF/9+gU2Sj5mm8XU5ex5uqd2TM+nyJLVZYoTXz1UmFw7IMQMXDwIa6PoidHkeysiJalIzHIDdZ7MB2cH95UM3cVODchKMBQKBQCAQCATlhhI7UJbhSMFZuJXngvhqKYRlL8KOr+Xb9TvCoM8hItGToVZppv6+nwKzjZiILNamvolBZ2DBPQtoGd/S30MTCMpEOF+rCU7nqxt5rwoRwfJjruR8NbsYO1ARMl/Lu3BLQa/TMvQW+UrcnC0ny8zdq6wUOnKFy9X5miY7X12NHQCo5xBqT5Vj6VZR7ICahVvl53y9kOvIfPWicCu9IJ3n/3yeJh804bN/PsMm2eh3TT/+fexfRt50LyBPUPeelwXNZok+FMYlCf79Fj7rJguvYfEw/DdZfHUhoL9RzaLjLSY0gO9H3iKEV4FAIBAIBIIqiiK+lnXOq6CIr7kmKyZrKSsfLx6G/3V3CK8a2QQw7DchvF6BNYcusHRvChqNxF7TRNBIzBkwh9saXn21mkBQkRDO12qCUrjlTh6ngjN2oKCUzNcyBE1FZMsz+TN2QP7D507mrVoMuakes1YeYe+5HP45nUXb+lUrj0aSJAocsQPuuKvDAxVXtWfHxWlHcVaDGq45X0EWav85ncWpjPLLfVUzdkBxvqbmGLHZJZeD/72hqHDLffE1z5zHrK2zeHvz2+SYcgDoVK8Tb9z2Bp3rdwbg3IVkAI6n5XE2U3b0JvnK+WrKgz/Gwm654Z1G3eCu/0FYTZd3ERqop1+LWhxKyeXTB9rSJC7cN2MVCAQCgUAgEPgdJXbA1Xl3RJABnVaDzS6RVWAhPuIK50e7foDFY+XYq9A4uOszaNxNzWFXGYwWGy8v2gdAtm4hFu1J3u75Nve2uNfPIxMIXEeIr9UET8qQFIoyXy8XyJziaxl/iIoyX/0YO6BkvvpBfI0JDaB/q0R+3nGWOZtPVjnx1Wixoxh6QwNc/1rxJo7CaLE5S6c8cb6eLkfna4aKhVtx4YFoNfIV+LQ8k09KsIpjs0tczHU/dsBkNfHpjk95fcPrXMi/AECr+Fa80f0N+jbpWyJ7WnEHHE7NA6BuTLDze0dVUvbKMQPpR0CjhW4ToNNY0Lr/nfDx0LZIkuR2hrZAIBAIBAKBoHLhdL66OGfUajVEhxhIyzOTnmcuOV8358OS/8LOb+XbDbvAXZ9DeLzaw64yfLL2GKczCrBp0snSf8fTNz/NuPbj/D0sgcAtROxANUHJfA1xQxhTiHAh87Us52tYoH9jB6w2O46/meUeO6CgFG8t2ZPMhZzyWzJeHuSbiz7XYDcKzbyJHTibWYAkyceWO6Jm/djyjR2QJIl0JfM1zPvYAb1O65zAnc/yfe5rep4JuwRajWvjt9ltzNk5h+s+vI5nlj3DhfwLNI5uzHd3fcc/j/1Dv2v6XSZY1rjEEdxc7cgBSYK/v4L/3SYLr+GJcnNsl+c8El4VhPAqEAgEAoFAUPVRxFedi5mvUGQuKFG6deGAPB/d+a1sBOj6EjywUAivpXAiLZ+P1x4BIMPwGYOa3c7M3jPFPFxQ6RDO12qCJ030ChFBivNVhcxXP8UOKOME/4mvzWtH0rZ+NDtOZTJv22nG9LzWL+PwBYVmpWxLh9aNZfDhiihvct/5WpT3GuLWH19FfFUiC3xNrsmKxXGRQg3nK0BCZBDJ2UaSs420UWWPV0cp26oZHljqUitJklh4cCET10xk/8X9ACSGJzK5y2QebvMwhlKaWmMueV9ULdsy5sDiZ2HvL/LtJj1h4KcQGqvecwgEAoFAIBAIqixWF1d7Fic6RJ7fpuebi/oGljwP1kIIqyWXajXs7JPxVhUkSeKFX/7GYoNC7T/c0EDLNwO/QedCR4NAUNEQ4ms1wZMmeoWi2IFSMl/LuAqoxA6YrXZMVhuB+vL9wjRZiomvLgal+4LhHRqw41Qm320/zahuTfwmBKtNvoeZwmFeOF9PpsuZrQ3ciBwAqBcjb38+u7BcjkWl5TQkQEeQG67g0kiICobTWeXifFXyXmuVEm+w6vgqXlr9EtvPbQcgOiiaFzu9yOibRxNiKDuPNyokAK0Gpzu9WW2VnK/Ju+SYgYzjoNFBj5eh/VNeuV0FAoFAIBAIBNUHu11yzlHd6VqIdazsys3Ogl9fhj0/yT9ofBsM/MytvoHqiMVmZ8afe9l+Ig8JCzHxK/nt3kUE6X0buSYQ+AohvlYTCjxooldQxNecK4qvrjU/KrEDIAttgWHlK76ai4Wk6/0ovvZpVou48EAu5JpYujeZ/q1r+20saqJkCrtTtgUlYwfczc9UYgMUJ6ur1AgLICRAR4HZxtnMQhrXDHPr8e6iRA5c6u70hsRIedKRku37+IrUXPk54q4gvv59/m8mrZvEqhOrAAgxhDDmljE81+E5ooKiXH4OnVZDTGgAaQ6h2mvnqyTBX5/D8pfAZobIunD3l1D3Zu/2KxAIBAKBQCCoViiRA4Bb55ExoQE01Zyi7+YXwXhaNgLcNgE6jhFGgDLYfiKDCQt2c+SCbLaxhy5h+YPfEB1ctXpTBNULIb5WExTnqzeZr6U7X0v/A6LTaggN0JFvtpFntFJDhexLd1DKtvzpegU58uC+dvWYtfIIczafrDriq+P4cqdsC4piB2x2iUKLza3jU3G+uiu+ajQa6seGciA5h1Pp+b4XXx2Cohp5rwoJkcEAJJeH+JpzednWgbQDvHniTbbu3AqAQWvg8RsfZ0LnCcSHeZZZpYivceGBxIV7cUW7MAt+ewoO/Cbfvq4f9P8IQmI836dAIBAIBAKBoFpitRetoCxrtacTSeLWnMVMCphBoNEi9w3c/SXUb++jUVYNMvLNTFtygJ93nAXARjbG4O9ZOeI16kXW8/PoBALvEOJrNaHQ4nC+uulMhLKcr67FDoAcPZBvtvmldMukiK8VYJn/fe3q8dGao/xzOotvtp6iZph6jsjSMOi0dGhcw213qisozmp39x0SoEOn1WCzS+QZrW6Jr0XOV/diBwDqx4Q4xFff575m5DvEVzWdr1GOwq3scogdcAi88eFBnMo6xZR1U5i7ay52yY4GDQ+0eoApt06hYXRDr54nNjQQyPPO9XpuB/z8EGSdAq0Bek6FW54AEcgvEAgEAoFAIPCA4s5Xl2IHjDnw+zP0PP4raGBPyC20ePw70TdQCnYJfvr7LG+vOEJWgaw55OqWkRf4HcsemE+rWq38PEKBwHuE+FpNcGa+eiO+XkE0VWIHXHGUhgfpScmBXKP75UreYq5A4mtceBD9WiSwaOd5Ji3cW67PPax9fab2b676fpXYAXdjLTQaDWGBerILLeQYrcS5qLtZbHbOOfJO3c18hfIt3Up3iK9qxg44na9Zvne+KgLvqtMLeG7LJMw2+fW0i2zH7P+bTevE1qo8T41w2VnbLNGDvFdJgq2fwIrJYLdAVH0Y/BXUbqvK2AQCgUAgEAgE1ROrrUh8NZQVF3B+p9w3kHkCu0bPNPP/sTfyfr4XwutVOZiSy/v7dJzYKhf21ogwssc4EbPuIN8N/I5uDbv5eYQCgToI8bWaUJT56kHsgCOXM89kxWqzO7Nu7HYJm+NKoCv5N85yJZM/nK+yOOjv2AGFsT2vJavAQn45vRfp+WZOpOX7TGx0Zr56UOgWHiSLr+6I8ucyC7HZJYIMWuLC3V/OXzu6/MTLotgBFcVXh/P1Qq6xxO+k2qTlZ7LleCqgY8nJ2Vi0Zro16MbUW6eSviudZjWbqfZcD3ZogNVmZ8jNdd17YEEGLBoFh5bIt5veCXd+AMFRqo1NIBAIBAKBQFA9UWIHNBrQXs35Kkmw/X/w5wRn38CeW97lf4vMXFdgK8fRVh7yTVZmrTzMl5tOYrNrCAnQ0a15Ph/v/z/Q2Xm759vc2+Jefw9TIFANIb5WExRxzN02eijKfAXZ/ao4+Cxu5t+EB8n78UfsgOJ8DTRUDPG1fmwocx4uv/KfP3YnM+q7f5zHgdp4U+gmHxeFbh0XzrzXmNCrT4JKoZajPCo5x/fia4ajcEvN2IEaoYEYdBosNonUXBO1o4JV2zdAoaWQj//6mLfWzCfENhEb2bRIjOXNHp/So1EPrFYrS3YtUfU529aPpm19N52qZ7bD/Ich+wzoAqD3G3DToyJmQCAQCAQCgUCgCorz9aqu18Is+G00HPhdvn3d7dD/Q/RZOmCjcxWcQEaSJJbvS+WV3/c5+ytaxdi5r5eBYYvvA42dZ9o9w7j24/w8UoFAXYT4Wk3IN3teuGXQaZ1lWdmFliLxtfgSDBdjB8BPsQO2ilG45S+CA+TXbbT4Snz1XNwvOi5cF1+L8l7dK9tSUJbtp5RDZmpR7IB6hVtarYZakUGcySgkOatQNfHVarfy1b9f8cq6VziXe45Iy72EAG0bhLJg5HY0FUXUtNthywewairYrRDdEAZ/DSpFIAgEAoFAIBAIBFAkvl4x7/XsDpj/IGSdlvsGer0K7R4HjYZYiywsZhaYsdsljwwjVY0zGQW8/Ns+Vh+8AEDdmGAm3349+/f8zMhlkzHbzAxOGszM3jMrznmHQKASQnytJhSYPC/cAtn9mm+2lSjdsliLO19dEF8dkQd5/nS+VoDMV3+gxAH4zvnqubgf4YEorzhfG9RwP+8VoFaksmzfhMVmd+n49RRfxA6ALCCfySjkfLb37l27ZGf+/vlMXD2RIxlHAKgbUZf6tsGcSYN7bmhTcSZA+emw8HE48qd8u9ldcMd7EORFUZdAIBAIBAKBQHAFlNgBffGVnpIEWz+GFS9ftW8gOlRe9WmzS+QarUSGGKiuSJLEp+uPM2vlYYwWOwadhse6NGZUtyYk557i3kWvkmPJoXO9zswdOBetpnqeswuqNkJ8rSY4xTEPMl9BLt1KzjaSXVx8dbhJtRrXmh/D/Zr5WnEKt/yBUrRW6OPYAU+cr2GB5e98jQ0NcC7bv5hrIlHlZfvFyXA4X9WMHQBIdAjIyVmeu3clSWL5seW8tOol/k35F4AaITWY0HkC97d4lFteXw9IdGpSQ40he8+pzTD/Ecg9D7pA6PsWtH1QxAwIBAKBQCAQCHyC1dFx4jRrFGTAwifh8FL5dlJ/uW8gqGRpbKBeR1ignjyTlfR8U7UWX7/ddpo3lx4E4JZGMbw2oAVN4sLILMzkjh/uIN2STtMaTVk0ZBFB+iA/j1Yg8A1CfK0meCOOQVHuawnx9dI/RGVQlPnqh9gBp/PVs9df2VE+90Kfxw54Urjl/nFRPPPVE7RaDfERQZzNLCQ52+gz8VWSJKf4GqOy+JrgGHOyh87XzWc2M37VeNafWg9AeEA449qPY2z7sYQHhrP6YCpWu0S9mBDqxngmcquG3Q4bZ8KaN0CyQew1csxAreb+HZdAIBAIBAKBoEpTInbg9Da5byDnrEt9AzGhAeSZrGQWVN/c1+MX83j9j/0AjOt5LaNva4JGo8FoNTLgxwHsT9tPjCGGxUMWEx0c7efRCgS+Q4iv1YR8LzI5QXa+AuQYL48dcDVH1ROHo1qYq7vz1VBxna+KIzrHxePCZpc4myG7PT11vgIkRMria4oKy/avRq7J6swbjlUx8xWKnK/n3XS+7kndw4TVE/j9sFwKEKgLZNRNoxjfeTw1QoocrhuPpAPQsUmsSiP2kLyL8OsIOL5Gvt3yHrh9JgSG+XdcAoFAdQoLC5EkiZAQ+bv91KlTLFiwgKSkJHr16uXn0QkEAoGgOmK129Fg50H7QvjqO9kIENNINgIktCr1sdGhAZzOKHDGkFU3LDY7Y37cidFip2OTWEZ1k4VXu2Rn2IJhrD+1nojACCY3mEzdiLr+Hq5A4MQXc1IhvlYDrDa7U3wM9cCZCBARdAXnq0NUMrgoaHpSrKQWpmpfuFXkfPVF4Lt3hVuK89W14yI5uxCzTc4K8saxWisyGMgk2YelWxmOiVZIgM75GahFrUj3nK/HM48zec1kvtvzHRISWo2Wh1o/xMu3vkzdyMsnO5uPpQHQ0Z+RAyfWwy+PQl4q6IPh9neg9VARMyAQVFH69+/PXXfdxeOPP05WVhbt2rXDYDCQlpbGzJkzeeKJJ/w9RIFAIBBUN/LT+NLwNt1su+Tbze+GO2ZBYHiZD1Vix6qr8/WjNUfZdTabiCA97wxu5TwHHbd8HD/v/xmD1sD8QfMp2F/g55EKBCXxxZy0eipR1YyCYkvNPRWAIq8QO6A4+vQuCnn+jB0wOd6D6up8LS6KmooVpalFgcmb2AH3CreUvNe6MSEuZQ1fjQQlM9WHztd0H0UOQPHxly4eJ+cmM+qPUVz34XXM2zMPCYnBSYPZ/+R+Pr/z8ysKrxdyjRxMyQWgQ2M/iK92G6x9E+b2l4XXmtfDyDXQ5n4hvAoEVZh//vmHzp07AzB//nzi4+M5deoUc+fO5f333/fz6AQCgUBQ7Ti1mesX9qObbhcmAuSS10GfuyS8QtE5gHJOUJ3YeSaLD1YfBeDVAc1JcBhHZm6ZyaxtswCYM2AOXRt09dMIBYKr44s5qXC+VgMUYUyn1RDoofjojB0oLHInKvk3rme++jF2wKZkvlZP8TWoWNZtgdmquguzwOKIHQj0PHbA1eNCyXttEOtZ3qtCrQhZvPRl7EB6ngmA2DB1IwcAp+s3Lc+MyWq7LM84szCT6Zum89629yi0ygJtr8a9eOO2N2ib2Pay/RVnyzE5cqBZYoRPhONSyU2RYwZOyFm0tLkf+r4NAX7OnRUIBD6noKCA8HD5hPbPP//krrvuQqvVcsstt3Dq1Ck/j04gEAgE1Qa7HTbOgDVvECDZOWZP4K3wF/ms7YNu7UaZR2dUs9iBArOVMT/uxGaXuKNVIv1b1wbgh70/MO7PcQC83fNt7m1xLxZL+RuzBIKy8MWctHoqUdWM/GJ5nBoPXWMRwY5czivEDrjqJlVEtjyTyHwtb7RaDUEG+bUX+CD31el8NbgvviqRFrkm95yv3uS9guvOUW9QyrZifSBgRocYnBcTigvIBZYC3tz4Jo3eb8Sbm96k0FrILXVuYc3wNSy/f3mZwivAxiN+ihw4thpmd5KFV0MoDPwU+n8khFeBoJrQpEkTFi5cyJkzZ1i+fLkzU+vChQtERET4eXQCgUAgqBbkXYBv74LVr4FkJ7XBAO4wv86ZgMZu78opvlaz2IE3lhzgRFo+tSKCeK2/XJC75sQahi0YBsAz7Z5hXPtx/hyiQFAqvpiTVk8lqpqhlCx5mvcKpccOGHTuxg4I8dUfKKVbRosPxFflGAv0JnbARedrmkrO18hycL76MHZAoynKvD2fZcRsM/PxXx/T+P3GjF81nixjFs1qNmPRkEVsfnizy0t6JEli09FyFl9tVlj1KnxzF+RfhLhmMHIttBpSPs8vEAgqBJMnT+a5556jQYMGtGvXjvbt2wOy46BNmzZ+Hp1AIBAIqjzH18lGgONr5L6B/h+z75bpFBDk8jlvcWJCHOJrNYodWHPoAt9uPQ3AO4NbERliYE/qHgb8OACL3cLdSXczs/dMj01hAkF54Is5qYgdqAbkmzxvole4kvhqccQO6LWuCZphgUXOV5td8iqv011MQnwlJEBPZoHFJ85XxV3tSZyBu6K8Ws5XRbhMzTX57HhUmk1jw3yzdD8hMogTafn8sncV9/8xnuOZxwFoENWAqV2ncl+L+9Bp3ftMTqYXcD7bSIBOy00Non0x7JJkn5NLtU5vlm+3fQj6TAOD52VqAoGgcnL33XfTqVMnkpOTadWqqEG6e/fuDBw40I8jEwgEAkGVxm6DddNh3VuABDWbwuCvIe56rPtSADw6V1AMGJnVRHzNyDfz3/m7AXioYwM6XVODM9ln6DuvLzmmHDrX68w3A79Bq6m+5+SCyoEv5qRCfK0GOJvoPcjjVIhQMl+LlSJZFeerm7EDIIt1ynLz8kBxvl6ai1mdUGIHClV2vkqS5HRXeyLwFy/ckiSp1KugkiRxKkN2vtb30vlaIywQnVaDzS6Rlmci3pEBqyYZ+Y7MVx84XyVJwqpJAzT876/55BiOEx8az6QukxjRdgQBOs+ec6PD9XpD/SiPCtTc4sgK+HUkFGZAQLjcHNvibt8+p0AgqLCsXr2aDh06UKtWrRL333zzzX4akUAgEAiqPLkpshHg5Ab5dpsHoO90Z+yV1e7oOXHRcFSc6GpUuCVJEi/9uoeLuSaaxIXxQp/rySzMpO+8vpzLPUdSzSQWDVlEkF79cy6BQG18MScV4ms1wCm+qhw74Mx8dXEJRpBBR4BOi9lmJ9foL/G1+l5lUz7/QpWdr2ab3Tkp8eQYU8RXi03CZLUTVEpu7IVcE0aLHZ1WQ+0o75yROq2G+PBAzmcbSc42+kR8LYodULdwa/2p9YxfNZ59JxsRxRBCtLV58bY3eLrd04QGeCdKb1LyXhv7MHLAZoHVr8Km9+TbtVrK7oJY97O0BAJB1eHOO+/EarVy00030bVrV2699VY6duxIcLBwwgsEAoHABxxdJRsBCtLkvoE7ZkHL/yuxiXKe44nzNbYaOV9//eccy/aloNdqmHVPa9BYGPDjAPZd3EdieCJLhy4lOrgcVtUJBCrgizmpEF+rAcULtzxFEV9zCi3Y7RJarQazI3bAoHNd0AwL0pORbybXaAHK72TK7BSKq6/4qmS+qu18LS7menKMhQbo0WhAkuTogdLEVyXvtXZUsCoRErUigzifbSQluxDqRnm9v0tRu3Dr3+R/eWn1Syw7ugyAaF0sWKF7/bsZ37mj1/u32SW2HE8HoOM1PhJfs87A/Ifh7Hb59k0joNdrYBBXwQWVH7vdTlZWlsvbR0VFofXASVNVyczMZPv27axbt45169Yxa9YszGYzN954I926deO1117z9xAFAoFAUBWwWWHtG7BhJiBBfHPZCFDjmss2VVZ76j3JfHVEj+WbbRgttlLPcyozZzIKePm3fQCM6XktSYnhDJk/hPWn1hMRGMHSoUupF1nPz6MUCFzHF3NSIb5WAwocma/eFG4pLlW7JIu54UEGLFblD5HrJ47hDvE1r5xLt0xWWSCszpmvSh6r2pmv+Y79Bei0bgnxClqthrBAPblGK7lGCzXDr+4SVSvvVSEhMhjIItlHpVtqZb4eST/CpDWT+HHfjwDotXpG3DCCHolPM/bHY6TlqvOZ7jufTXahhfBAPS1rR6qyzxIcXAILnwBjFgRGQv8PIKm/+s8jEPiJrKwsZi7+l6DQ8DK3NebnMvY/bYiJiSmHkVUODAYDHTt2pGPHjrz00kvs27ePt99+m3nz5rF161YhvgoEAoHAey7tG7jxYej9xlX7BqzOnhP3xdfwQD0GnQaLTSIj3+zsnKhK2OwS437eRZ7JStv60Yzs3JCxy8fy8/6fMWgNLLhnAS3jW/p7mAKBW/hiTirE12pAgcXzPE6FIIPWGRmQXWghPMiA1e5e7AC432yvFmZRuOVD56vnZVsKEUEGh/ha+nFxMl12vjbwMu9VoVak7LZM8YH4KkmS0/ka46Hz9WzOWaaum8qX/36JTbKhQcO9Le5latepNI5pzKGUXOCYauKxkvd6S+NYty6qlInVDCunwNaP5NuJN8DdX0JMQ/WeQyCoIASFhhMaEeXvYVRKDh8+zNq1a1m7di3r1q3DZDLRuXNn3nnnHbp27erv4QkEAoGgsnP4T1jwWFHfwJ3vQfNBpT5EiR3wZG6s0WiIDgngQq6pyoqvX2w8zvYTGYQG6Hj3/1rz/vZZvLdNjhabM2AOtzW8zc8jFAjcxxdzUiG+VgMKTN6LrxqNhohgA2l5JrILLdSJxrPYgUD5kCte3FUemETmq/PzV8RStVCctKFeHF+uivLqO19l8dUXztc8k9UZdxHrZuZrekE60zZO48PtH2KyyaVd/7n2P7x+2+slrhwnRMnjzy60UGC2el2Qtemokvca69V+SpB5Uo4ZOLdDvn3Lk9DjFdCrX0ImEAgqN9dffz01a9bkmWee4cUXX6RFixalljAKBAKBQOASNgusmgqb35dvJ7SCu79yqW9AMRwZPIgdANmEoYivVY0DyTm8s/wwAJPvSGJz8m88t+I5AN7u+Tb3trjXn8MTCDzGF3NSIb5WA5yZr4HefdyRwXrS8kzkFMr7U2IH3BFfwx3xBXkm4Xwtb4Kc4qtd1f3mO8R9b5yvReJr6aJ8ZXK+KpEDIQE6l9+bXFMu7259l3c2v0OuOReAzvU6M637NDrWuzzTNSLIQFignjyTlfNZRprEhXk8XqPFxl8nMwHopFbe6/7fYNFoMGVDUBQM+ASu76fOvgUCQZXj6aefZv369UydOpXFixfTtWtXunbtSqdOnQgJUeeim0AgEAiqGZf2Ddz8GPR6FfSumSOU2AGdhxntygq4zIKqJb4aLTbG/LgTs81Oj6bx1Iw9Sp95wwB4+uanGdd+nJ9HKBB4ji/mpEJ8rQYozldvnIkAEY7SrexCWSCzeBA+7rfYAVG4RYgjdqDAou57X+jYX6gX4r4iypd2XEiS5HS+NqihrvP1fHahKvsrTrobkQMmq4nZf8/m9Q2vc7HgIgCta7XmjdveoE+TPqVeZUuIDOLIhTySswu9El93nMrEbLUTHxFI45qe7wcAqwn+nAjbP5Nv17lJjhmIEkH7AoHg6syaNQuQs3M3bNjAunXrmDBhAvv27aNNmzZs2rTJvwMUCAQCQeXisr6BDyHpTrd24XS+epD5ChDtOBdQjBlVhZkrDnMwJZfY0ACGd9Hznx8HYrFbuDvpbmb2nilWrggqNb6YkwrxtRpQlPnqrfNVFshyHOKrkn/jjqAZHuiaw1FtTBbhfFXcl0a1C7cU56sX7Z2KKF9aHEVGvpk8kxWNBupEqyO+1oqUc5dSc4zY7RJaDydVV0JZWhRbivhqs9v4Zvc3vLz2ZU5nnwbgmphreLXbqwxuNhitpuzjNSEqWBZfs7xz7yp5rx2b1PBuspR+DOY/BMm75Nsdn4HbJoHO4NX4BAJB9cFms2GxWDCZTBiNRkwmE4cOHfL3sAQCgUBQWbCaYeXLsPVj+XbiDTD4K4hu4P6u7Irz1bP5sXIuUJViB7YcS+d/G44DMK5vAkMW9CbHlEPnep35ZuA36LTemb4EgoqCmnNSIb5WAwocS/y9yXyFIvFVcb6avYkd8JPzNVBfff8QKOJrgcria6GS+eqF8zUssGxH9EmH6zUhIoggL4Te4sSFB6LRgMUmkZ5vpma4e9mspZGeJ2e1xoZdvk9JklhwcAETV0/kQNoBABLDE3n51pd5qPVDGNwQKhNVcu8W5b16ETmw9xf47Rkw50JwDAz8FK7t5dW4BAJB9eHpp59m7dq17N+/n+joaLp06cKIESPo2rUrLVq08PfwBAKBQFAZyDwJPz8E5/+Rb7cfDd1f9rhvQIkd8LSMVlkFl1FFYgdyjBae+3kXkgQD28Tx+vZ7OJ97nqSaSSwasoggfZC/hygQeI0v5qTV1wZYjVAr8zXCIZwq7kQldsA98dVPsQMi89XpTC20qOx8dRxf3mW+lh07cMqR91pfpbxXkI/dmg5xVO3c16vFDqw8vpJ2n7dj0E+DOJB2gJjgGN7u+TZHnzrKyLYj3RJeARIc7l1vnK/ZBRb2nMsGZOer21gK4fdn5Twtcy7Uaw+PbxTCq0AgcIvk5GRGjhzJzp07uXjxIr/88gtPP/00LVu2FMsXBQKBQFA2+3+D2V1k4TUoCu79AXq/7lXRq9XmfeEWQEYViR2Y8ts+zmUVUjc6mL/zx7P/4n4SwxNZOnQp0cHR/h6eoBKwfv167rjjDhITE9FoNCxcuLDEzyVJYvLkySQkJBAcHEyPHj04cuRIiW0yMjIYOnQoERERREVF8cgjj5CXl1dim927d9O5c2eCgoKoW7cu06dPd3mMvpiT+l2J+uijj2jQoAFBQUG0a9eO7du3l7p9VlYWo0aNIiEhgcDAQK699lqWLFlSTqOtnBSq0EYPlztfLR78IQp3Crj+EV8Dq7H4GuIs3FJXfC1Q4fhypXDrpMp5rwpK7muyyrmvl8YObD+3ne5zu9Pzm578df4vQg2hTOw8keNPH+e5Ds8RbAj26HkSorx3vm45noYkQZO4MGcJmcukHYHPe8COrwANdB4HwxdDZG2PxyMQCKonP//8M6NHj6Z58+Z+eX4xJxUIBIJKitUIS56Hnx6Qi17r3CwbAa7r6/2uvYwdqErO1yV7kvn1n3NoNRAW9wsbz6wiIjCCpUOXUi9SdDsIXCM/P59WrVrx0UcfXfHn06dP5/3332f27Nls27aN0NBQevfujdFYZDYaOnQo+/btY8WKFSxevJj169czcuRI589zcnLo1asX9evXZ8eOHbz99ttMmTKFzz77zKUx+mJO6tfYgR9//JGxY8cye/Zs2rVrx6xZs+jduzeHDh0iLi7usu3NZjM9e/YkLi6O+fPnU7t2bU6dOkVUVFT5D74SkW/2vo0eriS+yn+I3HG+hjlEtjxTOWe+WuX3oDo7X4N85HwtUJzVXmQKR7jgiPaF8xVk5+ius9mk5KjsfHXEDljJ4q4f72LBwQUAGLQGnrjxCV7q/BLxYfFeP0+i4nz1wrmr5L12ctP1qtnzEyx9Hiz5EFID7voMmnT3eBwCgUDwzTffMHv2bE6cOMGWLVuoX78+s2bNomHDhvTv399nzyvmpAKBQFA5CTWlov+6L6Tuke9QuW9AEV/dOectTkxI1ch8vZBj5KUF8nvcpO5xlp3+GIPWwIJ7FtAyvqWfRyeoTPTt25e+fa98YUSSJGbNmsXEiROd8765c+cSHx/PwoULGTJkCAcOHGDZsmX89ddf3HjjjQB88MEH9OvXj3feeYfExETmzZuH2Wzmyy+/JCAggGbNmrFz505mzpxZQqQtDbXnpH5VombOnMmIESN46KGHSEpKYvbs2YSEhPDll19ecfsvv/ySjIwMFi5cSMeOHWnQoAG33norrVq1KueRVy6UzNdQLwu3IoIdpUiXOV8rT+xA9Xa+yu+92pmvyv68yRR2xg6UIso7na+x6jpfazmdr+qKr+ey5WX807dOZsHBBWg1Woa3Gs7hpw7zXt/3VBFeocj5mpxViCRJHu1j09F0ADo0jnXtAZYCWp/6HP1vT8rCa4PO8MQmIbwKBAKv+OSTTxg7diz9+vUjKysLm03++xIVFeVsnfUVYk4qEAgElQ/Nvl+59eAkNKl7ICQWhs6HnlNVLXpVMl89dr6GyeJrZiUWXyVJ4vn5u8kqsFAz0siKC2MBmDNgDrc1vM3PoxNUBHJzc8nJyXH+M5lMHu3nxIkTpKSk0KNHD+d9kZGRtGvXji1btgCwZcsWoqKinMIrQI8ePdBqtWzbts25TZcuXQgIKIocUS6qZ2ZmljkOX8xJ/eZ8NZvN7Nixg/Hjxzvv02q19OjRw/mmXspvv/1G+/btGTVqFIsWLaJmzZrcd999vPDCC+h0VxZ+TCZTiQ8+NzcXAIvFgsVSvu5Lf6GIYwFayavXHGqQhcusArPc+OZwUOo0ru83RC//0cop9Pz9Vx7nzuOVwi2NZK82n/ulGLTyxKHQbFX1PchzRAUE6jQu7/fSzzDYUPZxcSpNdr7WjgxUdfxx4fLk7HxmgSr7Tc1L5c3Nb7Lp1LUE0BgrWfS/tj+v3PoKSTWTAPeO3bKoGSJ/jeebbWTkFhIR7N5k83xWISfS8tFq4MZ6EWWP7eIhdL8+TP2MQ0hosHd+Dnun50Crg2r6u1UZ8eR7tDphsViQJBt2e9kXqyTJ5pxTePo4T8dY1fjggw/43//+x4ABA3jzzTed9994440899xzPnteMScVeIL4Hq38iM+wEmMpRLtiAvp/5wJgq9MO+8DPISJB9fmo2SqbhrR4di4dHiCfQ2cWmDGZzGg9FHH9ycoDF1h3+CJ6ncQu4xjQWnnztje5+/q7vf79Eb+HV8edeSX4Z06qPCYpKanE/S+//DJTpkxxe38pKSkAxMeXNCrFx8c7f5aSknLZqiS9Xk9MTEyJbRo2bHjZPpSfRUeXnk/sizmp38TXtLQ0bDbbFd/UgwcPXvExx48fZ/Xq1QwdOpQlS5Zw9OhRnnzySSwWCy+//PIVHzNt2jReeeWVy+5fv349+/fv9/6FVAJyjTpAw9ZN6znsRZn7kWwNoON8WhZLlizh1GktoOXI4YMsyTvg0j7OFwDoycgt8DoXbcWKFS5tZ5fAYpMP9Q1rVxOm3oXQSsWJXAA9aVm5qmbSHTspHwcnjx1iScGVf3evhvIZHsuRx5aSnn3FsRVYIatQ/gwP/LWB494laJQgJU0+rvedOMeSJWc83k++LZ+FFxby+8XfMdqN1LZ/DcDoesPoFFKPk3+d5CQnVRnzpYTodRRYNfy0eAWJbqYybL0gv/56oRIbVpf+O1U3fQMtz8xBK5kx6iPZ0eAJ0vKSYNlyzwcv8Cuufo9WN3Jzczl2TktQaHiZ2xrzc1lhPEZ4eLjHj/OEtLQ0jx5XkTlx4gRt2rS57P7AwEDy8/N99rxiTirwBvE9WvkRn2HlIsyYzI0nPiTSeAYJDYfj7+BQjYFIG/8F/lX9+Y47znWOHz3CEtNhtx8ve4D02CWY//vSSnkuOuew/B5kaX7Doj3Df2r8h+vSr1P1nFL8Hl6OO/NK8M+cVJmP7t+/n9q1izo/AgO9EJ4qAL6Yk/o189Vd7HY7cXFxfPbZZ+h0Otq2bcu5c+d4++23rzrRHT9+PGPHjnXePnfuHElJSXTp0oUGDRqU08j9h8Vmx7ZlJQD/6d2TqBDPv+33J+fw4f6t2HWB9OvXlT9/3A1pKbRs3ox+t7gWsJ2cbeStXesxS1r69u3lUVOcxWJhxYoV9OzZE4Oh7NdjtNhg6yoA+vbu5Yw+qG4cSM5l1t4taA3y56cWCzP+gfQ0bmzVgn431nHpMZd+hgdTcnl/3xbnsXUpe85lw1/bqBkWwMA7eqk2doCaJzOZe+QvLPow+vXr5PbjCy2FfLzjY97e8jYZhRkA3FCrLdmnamC1w6j+w6kd5VmZlqt8cmILB1NyadLqJrpeW9Otx678eTeQQr+2jenXo8mVNzLnoVv2AtrTPwJga9CFtWGD6dLvbpd+BwUVD3e/R6sbGRkZnNhwnJDwqDK3LcjNomfnRsTExHj8OE84efKkR4+ryDRs2JCdO3dSv379EvcvW7aMpk2b+mlUV0bMSQXie7TyIz7Dyodmz0/olk5FY8lHCq2J6fYPOHjE7NPPcMOCfZB6jqTrr6PfrY082seUXavJMVpp2+FWGtdUt7/C15isdl78exUgkavdwF3X38W8AfPQadVxw4jfw6vjzrwS/DMnVeaj4eHhREREuP34S6lVqxYAqampJCQkOO9PTU2ldevWzm0uXLhQ4nFWq5WMjAzn42vVqkVqamqJbZTbyjal4Ys5qd9UqBo1aqDT6a74hlztzUhISMBgMJRYztW0aVNSUlIwm80l8hwUAgMDS6juOTk5ABgMhmrxy11gLbKOR4YGYfAi8zQmTBaQso1WDAYDVke+ZFCA3uX3MjpM/q/FJmHX6JwlUJ7g6mdYUCxeNjQ4AINeRdtkJSIiRP49KLTYVT32jRb5OAgPCXR7v8pnGB0m55bmmqxX3MfZbDkjqUGNUNV/b+vGygdlSo4RvV7v8gUBi83CVzu/Yuq6qZzLPQdA0xpNee221+jR4D+0fEW+ehsfGYrBi+PcFWpHBXMwJZcLeRa33h9JkthyXM686Xxt3JUfm7IX5j8EaYdBo4VuL2G/5WlMS5dVm+/Rqoz4DK+MwWBAo9GhdeHEQqPROd9HTx/n6RirGmPHjmXUqFEYjUYkSWL79u18//33TJs2jc8//9xnzyvmpAJvEJ9f5Ud8hpUAcwEseR52fivfbtAZzaDP0QXFwpElPv0MHX1bBLpxznspMaEB5Bit5JjUPQ8rD37dvZdCi4SVdG5uUJN5g+YRpA9S/XnE7+HluDOvBP/MSdX+zBo2bEitWrVYtWqVU2zNyclh27ZtPPHEEwC0b9+erKwsduzYQdu2bQFYvXo1druddu3aObeZMGECFkvR+fGKFSu47rrryowcAN/MSf3WPhQQEEDbtm1ZtWqV8z673c6qVato3779FR/TsWNHjh49it1ud953+PBhEhISrjjJFRQ10eu1GgK8LJuKdLhmzVY7RosNi8395sfQAD2KtlVepVtK2RZAgIctlVWBYEchVqHF5nEx05VQjrEQLwRGpXDLbLVjsl6eS6PkvdaPVf9KcVyEfCJsstrJKig758Yu2flh7w8kfZzEY4sf41zuOepF1uPLO79k9xO7uavpXWQ69hMSoHO+776kqHTLvdKww6l5pOWZCDJouaF+VMkfShL8/RV83l0WXsMTYPhi6PK8LMIKBAKByjz66KO89dZbTJw4kYKCAu677z4++eQT3nvvPYYMGeKz5xVzUoFAIKjAXDgA/+vmEF410HU8DFsE4WW719TAalcKt7wwMYXKfxcyKlnpVmZhJhOWzAcgKOwgv927yCfCq6B6kZeXx86dO9m5cycgL/HfuXMnp0+fRqPR8Oyzz/Laa6/x22+/sWfPHoYNG0ZiYiIDBgwA5Ivdffr0YcSIEWzfvp1NmzYxevRohgwZQmJiIgD33XcfAQEBPPLII+zbt48ff/yR9957r8QKpNLwxZzUr+uvx44dy/Dhw7nxxhu5+eabmTVrFvn5+Tz00EMADBs2jNq1azNt2jQAnnjiCT788EOeeeYZnnrqKY4cOcIbb7zB008/7c+XUaHJN3nfRK8QFqBHq5Gv/mUXWrA4SqwMOtejA7RaDWEBenJNVnKNFmqG+z4LRCnbCtBrPYo5qCooIqDNLmG22QlUyQGsFLp5c4yFBRZ9FeUZrQSGldzXyfQCABrEhnj8HFcjUK+jRlgAaXlmkrONRIde+aRZkiSWHV3GS6tfYmfKTgBqhtRkQucJPH7j4wTqi47ltDx5YhVzlX2pTUKk7Eo/n13o1uM2HpUzem5uGFvyeDDmwOJnYe8v8u0mPWHgbAitocZwBQKB4KoMHTqUoUOHUlBQQF5e3mWFCr5CzEkFAoGggiFJsHMe/PEcWAshLB4GfQ4Nu5TrMKx29895L6Uyiq9Gq5H+P9yFKX8kOmDGnfcTHVy2Y1AgKIu///6bbt26OW8rgujw4cP5+uuv+e9//0t+fj4jR44kKyuLTp06sWzZMoKCioT/efPmMXr0aLp3745Wq2XQoEG8//77zp9HRkby559/MmrUKNq2bUuNGjWYPHkyI0eOdHmcas9J/Sq+3nPPPVy8eJHJkyeTkpJC69atWbZsmbPw4PTp02iLXWGqW7cuy5cvZ8yYMbRs2ZLatWvzzDPP8MILL/jrJVR4FFdiaKD3H7VWqyE8yEB2oUVupXeKr+5dBQwPUsTX8nG+miyyOBhYjV2vAMHFnKlGsw/EVy+OMZ1WQ1ignjzHcREbVlKUP5XuO+crQK3IIIf4WkhS4uVZNZtOb2L8qvFsOL0BgPCAcJ7r8BxjbhlDeODlweTKxCq2nMTXRA+dr5sc4munJrFFdybvgp8fhIzjoNFB98nQ4Wnw4mq/QCAQuEtISAghIepfcLsaYk4qEAgEFQhTHvwxDnb/IN9ufBsM/AzC3Os2UAOrTXG+ei++ZhZUDvHVLtkZtmAYf53IJJ4IIoO1/Kd5xcpeF1ReunbtWupKXI1Gw9SpU5k6depVt4mJieG7774r9XlatmzJhg0bPB6nglpzUr83D40ePZrRo0df8Wdr16697L727duzdetWH4+q6qCGK7E4kcGy+Co7X92PHQAIC9JDdjnGDhRzvlZnDDotBp0Gi02iwGIlEnXyWZyxA14eY+FBReLrpRQ5X30kvkYEs/dcDsnZJcXL3am7mbB6AosPLwYgUBfI6JtH82KnF6kRcnUXaEa+CSh/52uyG85Xi83OtuPpAHRoXEN2F/z1OSx/CWxmiKgDd38J9dr5ZMwCgUAAcMMNN7Bq1Sqio6Np06ZNqStU/vnnH5+ORcxJBQKBoAKQslc2AqQfcfQNTIBOY/1mBFBiBwxexQ7IxpL0vIovvkqSxNjlY/l5/8/UsI8CoG/z2l6JzwJBZcDXc1K/i68C31IkjKnzUUcGy4Jd8dgBd3NUlXzPPFPZ+ZpqoGS+BlZz8RUgyKDDYrNSaL48V9VT1BL4w4P0JGdDrrHkcZFnspKWJ4uZ9XwQOwCQECk7R1Mc4uuxjGNMXjuZ7/d8j4SETqPj4TYPM/nWydSJqFPm/pTYgUsdvL4i0Sm+yoHgrsRr7DqTRb7ZRnSIgaRoCX4eDvsXyT+8ti8M+BhCPGthFwgEAlfp37+/s4Sqf//+1ToeSCAQCKo1kgQ7voalL4DNBOGJcPcXUL+DX4elnPN653yVz38Vg0ZFZuaWmby37T2QNNTS9ybXCn2al0++rkDgT3w9JxXiaxVHzcxXgIhg+ZDJMRY5X/Vu5t+EByn7KN/CrerufAX5OMg1Wp2CqbfY7BImx/vrrcCviPKXHhdK5EB0iMEp/qtNLYf4ejw9gyf/eJL//fM/rHZ5HPc0u4ep3aZybey1Lu+vvGMH4iOLSsMyCywuOW6VvNchddLQftYFsk6B1gA9X4FbngQhgAgEVYpp06bx66+/cvDgQYKDg+nQoQNvvfUW1113nXMbo9HIuHHj+OGHHzCZTPTu3ZuPP/7YufQe5OX3TzzxBGvWrCEsLIzhw4czbdo09PqivwFr165l7Nix7Nu3j7p16zJx4kQefPDBK47r5Zdfdv7/lClTVH/dAoFAIKgEXNo3cE0vGDAbQmNLfVh5YLN7ds5bHMX5muFCua8/+WHvDzy34jkAxrT9gF83aQkP0sur5ASCKo6v56RCjariKA5HNTJfoZjztcDzzFelXKncYgeE+OpEyX01WtQRXxVnNajjfIXLna+nHZEDvsp7BYgIlt+PhfvW8snfn2C1W+nTpA//jPyHH+7+wS3hFYrE1/KKHZBLw+RJ3fks16IHNh25yEO6pTx35ilZeI2qBw8vh/ajhPAqEFRB1q1bx6hRo9i6dSsrVqzAYrHQq1cv8vPznduMGTOG33//nZ9//pl169Zx/vx57rrrLufPbTYbt99+O2azmc2bNzNnzhy+/vprJk+e7NzmxIkT3H777XTr1o2dO3fy7LPP8uijj7J8+fIyx/joo49ecXm/QCAQCKowybvgs1tl4VWrh55T4d4fK4TwCkWZr+6e8xanMjhf15xYw7AFwwB4pt0zRNEVgJ5N48V5tKDa4Ys5qXC+VnHyHeJYsIqZrwDZhVYvCrccsQPlVbglxFcnwQ53qlrOV2U/Wo33sQ7KcXGpKF+U96p+5EC+OZ/3t73PjLW/EcZENPZoOtTtwLTu0+hS3/MmVSUmobxiB0Au3UrLM5GcbaR57chSt83PusjI5Mn0NPwNEtD0DrjzQwiOKpexCgQC9cjNzSUnJ8d5OzAw0LlkqjjLli0rcfvrr78mLi6OHTt20KVLF7Kzs/niiy/47rvvuO222wD46quvaNq0KVu3buWWW27hzz//ZP/+/axcuZL4+Hhat27Nq6++ygsvvMCUKVMICAhg9uzZNGzYkBkzZgDQtGlTNm7cyLvvvkvv3r1LfS0XL16kT58+1KxZkyFDhnD//ffTqlUrb98igUAgEFRELu0biKwr9w3UvdnfIyuB1a5G7ID8dzkzv2I6X/ek7mHAjwOw2C3cnXQ3M3rNoMv0dQD0FpEDgmqIL+akQo2q4ijiWKhasQPOpeEWLFbPMl8jruJw9BUmZ+arOu9BZSbYIH9Whao5X5XjS+91JsrVHNFK7ICazlezzcxH2z+i8fuNeWn1S2RbTwEQqqvDhgc3eCW8QvnHDkBRbm2ZpVtn/kL3WRd6av/GjB76vg3/940QXgWCSkpSUhKRkZHOf9OmTXPpcdnZ2YDcFguwY8cOLBYLPXr0cG5z/fXXU69ePbZs2QLAli1baNGiRYkYgt69e5OTk8O+ffuc2xTfh7KNso/SWLRoEcnJyUyaNIm//vqLG264gWbNmvHGG29w8uRJl16XQCAQCCoBhVnw0zBY8pwsvF7XDx5bX+GEVyhWuOVN7ECIfE6QXgGdr2eyz9B3Xl9yTDl0rteZbwZ+w77zuZzLKiQkQMet19b09xAFgnLHF3NSIb5WcdQu3IooXrjlYf5NuccOeFgMVhVRjgO1CrfyTeo5q68myp90iK8NanjvfLXZbXy7+1uu//B6Ri8dTWp+Ko2iG/G//m8DYLZqyDV5/96Ud+wAQIKjdOt8lvHKG9jtsOk9+KoPQQXnOWmP59Mms6HdSBEzIBBUYvbv3092drbz3/jx48t8jN1u59lnn6Vjx440b94cgJSUFAICAoiKiiqxbXx8PCkpKc5tiguvys+Vn5W2TU5ODoWFZceiREdHM3LkSNauXcupU6d48MEH+eabb2jSpEmZjxUIBAJBJeDcDvi0Cxz4Te4b6D0NhnxXYYteldgBndaL2IEw+ZzAaLGXiG3zN5mFmfSd15dzuedIqpnEoiGLCNIHsXSv/De923VxBBmEgUlQPVF7TipiB6o4ahduRRYXXz2OHZAPuzyTyHwtb5Q/nmo5X5X9qJEpXJT5eqnz1fvMV0mS+P3w70xYPYG9F/YCUCusFpO6TOLRGx4lQBfAe4v/JLPAQkq20atiL0mSSM9zOF/Dyk98TYwqxfmanw4Ln4AjcubiWkNnRucOZ1qLjuU2PoFA4BvCw8OJiIhw6zGjRo1i7969bNy40Uej8h6LxcLff//Ntm3bOHny5GWCrkAgEAgqGZIEWz+BFZPBboGo+jD4K6jd1t8jKxUldsDgRexAaICOAL0Ws9VORr5ZNWOUNxitRgb8OIB9F/eRGJ7IsqHLiA6ORpIkljnE1z4ickAgUG1Oqqoa5YqjQVC+KFfWVC/cKvQ8diC8WHRBeWCyygKhEF+LRHi1Ml+dzlcVrog6M19NRceF0WIjOVt2cjbwUHxdd3IdHb/sSP8f+rP3wl6igqKY1n0aR586ypM3PUmAThZIazmco2Uu2y+DPJPV6baODS2/zFfF+Zp8qfP11BaY3UkWXnWB5PZ4mwdzHyePEDo0rhhFBgKBoPwYPXo0ixcvZs2aNdSpU8d5f61atTCbzWRlZZXYPjU1lVq1ajm3SU1Nveznys9K2yYiIoLg4OAyx7dmzRpGjBhBfHw8Dz74IBERESxevJizZ8+6/BrFfFQgEAgqGAUZ8MN9sHy8LLw2vVOOGajgwisUd756Lr5qNBpn9ICyQs6f2CU7wxYMY/2p9UQERrB06FLqRtYF4HBqHifS8gnQa+l2fZyfRyoQ+A815qTFUUWNMplMzJgxg4YNG6qxO4GKKCKbWs5XJXYgp9CCRWl+1LsZO3AVh6OvMDszX4X4qoikRrWcr0rma6Aa4uvlx8XpjALnz6JD3HOj/pP8D32+7UPXOV3ZcnYLwfpgxncaz/Gnj/NipxcJDSgp5iqZqSnZV1m27yLKhCrYoFOt6M4VFOfreUU8ttthwwz4+nbIPQ+xTWDEKlaH3Q5oSEqIKNdCMIFA4F8kSWL06NEsWLCA1atXXzZna9u2LQaDgVWrVjnvO3ToEKdPn6Z9+/YAtG/fnj179nDhwgXnNitWrCAiIoKkpCTnNsX3oWyj7KM0ateuTb9+/UhLS+Ozzz4jNTWVL7/8ku7du7uUKy7mowKBQFABObNdjhk4tAR0AdDvHfi/uZWmb8DqjNrz7lxSiSPzt/gqSRJjl4/l5/0/Y9AaWHjPQlrGt3T+fOneZAC6XFPDGRcoEFQ3vJ2TXgmXf5tMJhNTpkxhxYoVBAQE8N///pcBAwbw1VdfMWHCBHQ6HWPGjPFoEALfUbwQSQ0ii4uvjiUYejfzb0TsgP8Idjpf1Xnv8x3HV7AKx1eRI7pobEWRAyEuf8kdSjvEpDWT+Hn/zwDotXpG3jCSiV0mkhCecNXH1XIWVnknvqb5IXIAipyvqTlG7LkX0C58DI6tln/Y8h64fSYEhrFp4y4AOl1To1zHJxAI/MuoUaP47rvvWLRoEeHh4c6M1sjISIKDg4mMjOSRRx5h7NixxMTEEBERwVNPPUX79u255ZZbAOjVqxdJSUk88MADTJ8+nZSUFCZOnMioUaMIDJQv5jz++ON8+OGH/Pe//+Xhhx9m9erV/PTTT/zxxx9ljnHKlCkMHjz4stzZ4oj5qEAgEFQS7HbY8gGsmgp2K8Q0gsFfQ4J3jeHljdUZteddR0JFEV9nbpnJe9veA2DOgDl0a9itxM+LIgeuft4kEFR1XJmTuovLisnkyZP59NNP6dGjB5s3b2bw4ME89NBDbN26lZkzZzJ48GB0OhHGXNFQsxAJisTX9HwzknwR0O3YgQhleXk5xQ4I52sRwSrHDhQqsRYqHF/hVyjcOuUo23Il7/VM9hleWfcKX+/8GptkQ4OGoS2H8krXV2gU3ajMxydElJKZ6gbKhCq2HMu2AOLCA9FqoK20D2n2s5CfCvpg6Pc2tLkfNBokSWLjkTQAETkgEFQzPvnkEwC6du1a4v6vvvqKBx98EIB3330XrVbLoEGDMJlM9O7dm48//ti5rU6nY/HixTzxxBO0b9+e0NBQhg8fztSpU53bNGzYkD/++IMxY8bw3nvvUadOHT7//HN69+5d5hhHjBgBwNGjRzl27BhdunQhODgYSZKcF+DEfFQgEAgqAfnpsPBxOPKnfLv5IPjPLAhyL6O8IqA4X72JHYCKIb7+sPcHnlvxHADv9HyHe1vcW+LnJ9LyOZiSi16roUdTETkgqL64Mid1F5fF159//pm5c+dy5513snfvXlq2bInVamXXrl0eP7nA9xSouCwcihrpTQ5BEzyIHQgs39gBk4fZtFWREJVjB4qcr76JHTjpEF8bxIZc9XFpBWlM2zCNj/76CJPNBMAd197B67e9Tov4Fi4/v1rO14x8eQwx5Sy+6jUS40N+42Hrj+jyJahxHfzfHIhr6tzmZHoB57ONGHQabm5YMRtlBQKBb5CUK6alEBQUxEcffcRHH3101W3q16/PkiVLSt1P165d+ffff90eY3p6Ov/3f//HmjVr0Gg0HDlyhEaNGvHII48QHR3NjBkzxHxUIBAIKjqnNsP8R+TYK30Q9HkT2j4IlfQ7WhFf3S2ZvhR/i69rTqxh2IJhADzT7hnGth972TaK67V941iiQsr3XEYgqEi4Mid1F5e/Qc6ePUvbtnIgdvPmzQkMDGTMmDFiolvBUZaXq9WoGHGFFnh3/xApIluB2YbNXvbJoLco5UcidkB956uasRZXckQXxQ5c7nzNNeXyytpXaPReI2ZunYnJZuLW+rey6eFN/Hbvb24Jr1C0bN/bzNd0xflannmquanwzQBG2H5Ap5E4W/8uGLmmhPAKsOmo7Hq9oV50hWhZFQgEguKMGTMGg8HA6dOnCQkpuuh2zz33sGzZMkDMRwUCgaDCYrfD+nfg6/84+gaugUdXwY0PVVrhFYpiByqz83VP6h4G/DgAi93C4KTBzOw984p/N5c58l77NK9V3kMUCCoUrsxJ3cXls2+bzUZAQNHVD71eT1hYmEdPKig/1C7cMui0hAbonI5HAL2bf4iUbE+APKOVSDeLlNylKHZALENUxNdCtcRXkyLuq+d8NVrsWGx2DDptMedrkfhqtBqZ/fdsXt/wOmkFDjEx4QbeuO0NejXu5fEJeC2VCrfS88o5duDYGvh1BORfxKQJ4kXTQzS/5jEeCbhcsFbE105NRN6rQCCoePz5558sX76cOnXqlLj/mmuu4dSpU4CYjwoEAkGFJO+iPB89vka+3XII3D4DAiv/97PT+epmz8ml+Et8PZ19mj7z+pBjyqFL/S7MHTgXreby13Iuq5BdZ7PRaKBXkhBfBdUbV+ak7uKy+CpJEg8++KCzUMFoNPL4448TGlryBP/XX3/1aCAC35BvUtf5CrL7VRFfDTqN22JXgF5LoF6LyWonx2jxufhqEoVbToIdsQOFKsUOFFjUix0o3qaZa7QSFqjnXKacv9ogNgSr3crcXXOZsnYKZ3LOAHBt7LW81u01BiUNuuIkwh0U8TXXZCXXaClxkcAdlAmVz2MHbFZY96bsMECCuGZ8FTeRBX9LxGZdnltrs0tsPpYOQAchvgoEggpIfn5+CXeBQkZGhnP+KeajAoFAUME4sR5+eRTyHH0Dt78DrYdWardrcaw2WXzVV8LCrczCTPrO68v53PM0q9mMhfcsJEgfdMVtlciBmxrEUDO8HFfwCQQVEFfmpO7isiI3fPjwErfvv/9+j55QUL4oIptama8gl24puZieZt+EB+kx5ZnJM/k+99Vkld8DIb4WOVTVcr4Wqhg7oNdpCQnQUWC2kWe0klVgxi7JgvH6M38wae1EDqYdBKBORB1evvVlHmz9IHqtOhcWwgL1hAfpyTVaSc0xeiy+lkvsQM55eZJ7apN8u+2D0OdNAralAPuvmFu773w22YUWwgL1tKoT6buxCQQCgYd07tyZuXPn8uqrrwKg0Wiw2+1Mnz6dbt3kNmYxHxUIBIIKgt0G69+GdW+BZIea18Pgry+LvarsWO2ykcfd1Z6X4hRfC8pHfDVajQz4cQD7L+6ndnhtlg5dSnRw9FW3X+4QX/uKyAGBwKU5qbu4rFp89dVXHj2BwH+YrXYsjit1IQZ1na8Knv4RCg8ykJZnLpfSLbMo3HISZFA381VxVqvhfAVZlC8w28gxWriQIwuIZs05Bs9/FIDY4Fhe6vwST9705FWv2npDQmQQucY8krONNIkL92gf6Xly4ZbPYgeOrIQFI6EgHQLC4I73oMXdACRGye/J+ezLna+bjsqu11saxaIXvwsCgaACMn36dLp3787ff/+N2Wzmv//9L/v27SMjI4NNm+SLTWI+KhAIBBWA3BQ5ZuDEevl2m/uh79sQcPWS3MqI3S6hVJR4O38uT+erXbLzwIIHWH9qPRGBESwdupS6kXWvuv2FXCN/ncoAoHczIb4KBK7MSd1FNK5UYZSyLVBPHAPZ+argqZu0qNneUsaW3uPMfDUIwUmJnzCqFDugtrM6PMhAao6J7Wd289GWhcBt5FqPExYcxthbxjKuwzgiAiNUea4rkRAZzOHUvCs6R13FZ7EDNgusfg02zZJv12oBg+dAbGPnJkppWHLW5eMvynuNVXdcAoFAoBLNmzfn8OHDfPjhh4SHh5OXl8ddd93FqFGjSEhI8PfwBAKBQABwbDX8OhLyL4IhFP4zE1oN8feofIK1WDm0WoVbWQUWrDa7z8wQkiQxdvlY5u+fj0FrYOE9C8ssIv5zXyqSBK3qRpEYFeyTcQkElQlfzEmF+FqFUdyNATqtqkvuI4otx/Y0dkDJ9yyP2AGzTThfFYJ95XxVyVmt18li/OglzxNka0UE0Kp2It89eJyaoTVVeY7SSPCydEuSJGfsgKria9YZ+OUROLNNvn3TCOj1GhhKun8THM7XC7nGEpM6o8XG9pPy1eyOIu9VIBBUQCwWC3369GH27NlMmDDB38MRCAQCwaXYrLB2GmyYAUgQ3xzu/gpqXuvvkfkMJXIA5K4Tb4gqZmDKKrRQw0cRZTO3zOS9be8BMHfgXLo1LHuJ9DIROSAQOPHVnFSoUVUYxfkaomLeK5R0vnqT+QqQUw6xAyaLKNxSUBzQqhVumdVxvp7MOsnwhcP5N3UzADrCaBh+MwAP3XhHuQivUFS65anzNc9kdTqtY8NUEl8PLYVPO8vCa2CE7Ha9/Z3LhFeAGqGBGHQa7BKk5pqc9+84lYnZaicuPJAmcZW/dVYgEFQ9DAYDu3fv9vcwBAKBQHAlcs7DnDtgg6Pote1D8OjKKi28grrOV71OS5SjaNpX0QPf7/me51Y8B8A7Pd9hSPOyHclZBWa2HJfjyfqIyAGBwGdzUqFGVWHyTbIwFmLwnfjqaeujUmZULrEDDudroBBfi8RXlZyvivga4mGsRWpeKk8teYprP7iWubvmYtfkAzCh42tE6uXl9A1iyy87qsj5enlmqisoE6lgg84Z8eAxVjMsnwDfD4HCTEhsA4+th2YDrvoQrVZDfIRDQM4qeg1FkQM10FSR5lmBQFD1uP/++/niiy/8PQyBQCAQFOfICpjdCU5vhoBwGPQF3DELDFV/ebrVViS+GrTen0v6Mvd19YnVDF8ol1I+2+5ZxrYf69LjVuxPxWaXuL5WOA1qhKo+LoGgMuKLOamIHajC5Dudr+p+zBHBRfvzdCm/M3agHAu3AvXqitCVEUWIN9vsqmQNFYmv7h1jWcYs5iXPY+gnQ8m3yIJrz0Y9qUdvVu4rJEgXw5nMowDUL8dJQC0lM9VD56tqkQOZJ2H+w3Buh3z7liehxxTQl708KTEymLOZhZwv9hoU8VVEDggEgoqM1Wrlyy+/ZOXKlbRt25bQ0JLf/zNnzvTTyAQCgaAaYrPA6ldhk7yEnVotYfDXJfoGqjpWh4lHq5FNDt4SExLAcfJVF193p+5m4I8DsdgtDE4azIzeM1w2XBRFDohsdYFAwRdzUpcUk99++83lHd55551uD0LgGxR3Y6iKZVugTuxAhLNwq/zEVxE7ULJ4rdBiI9xr8dUh8Lt4jBVYCvhw+4e8ufFNMo2ZANxc+2amdZ/GbQ1v4/U/9gMnOJSSi8UmEaDXkhBx+fJ6X+F0vuZ4KL7myROpGt5EDhz4HRaOAlM2BEXCgE/g+ttdfriS+6o4X7MLLOw+lw0I8VUgEFRs9u7dyw033ADA4cOHS/xMo9GI+ahAIBCUF1lnZCPA2e3y7ZtHQs9Xrxh7VZVRYgf0KrhewTfO19PZp+k7ry85phy61O/C3IFz0WpcG2+u0cKGI7JJo28LETkgECiUNSf1BJfE1wEDBri0M41Gg82mznJmgffkO8TXYJ+Kr5UndkCIr3L0gkYDkuQQX4uVp7mL3S45s2PLcr5abBa++PcLpq6bSnJeMgB1g+oy8/aZDGo2yPkFpoxn73lZLKwXE6LKTwz1awABAABJREFUVWZXUTJfswosFJptbv/uZOTLOaseOV+tJvhzEmz/VL5d5ya4+0uIqufWbhIuce9uOZ6GJEHjmqHO1ycQCAQVkTVr1pT6c62LJ79iPioQCARecHAJLHwCjFkQGAn9P4Ck/v4elV9QYgc8jdq7FLXF18zCTPrO68v53PM0q9mMhfcsJEjv+nx/zaGLmG12GtUM5RrRCyEQOClrTuoJLomv9mItf4LKQ4GjiT7U2+zJS4gokfnqYexAOTpfTQ6B0NOIhKqERqMh2KCjwGzzOvfVaLUhOWKQruZ8tUt2ftz7I5PWTOJY5jEA6kfWZ3KXyUSdjuKO6+4oceVIKWI7kyG7Nssz7xUgPFBPaICOfLON5OxCGtV0bxJSFDvgZntp+jGY/xAk75Jvd3gauk8GnfvieKLD+Xre4XzddFQO0O8kXK8CgaCSI+ajAoFA4EOsZlg5BbZ+JN9OvEE2AsQ09Ouw/InV8XfH27ItBTXFV6PVSP8f+rP/4n5qh9dm6dClRAdHu7WPZXtlU0yfZrVEL4RA4GNE5msVxpnHqXLma3Hnq6eCpiKy5ZrKIXZAKdwyCPEVZKG0wGxzulY9paCYeBt8SambJEksObKECasnsCtVFhTjQuOY2HkiI9uORCtpWXJmyWX7vNSJWy+mfEPfNRoNtSKDOHYxn5Rso/viqyexA3t/hd+eBnMuBMfAwNlwbW+3nrc4lzpfRd6rQCAQCAQCgaBUrtg38ArovewxqOQosQOeRu1dilriq12y88CCB9hwegMRgREsHbqUupF13dpHodnGmoMXAZH36mvsdjtZWVluPSYqKsonYxH4D49Uufz8fNatW8fp06cxm0t+cTz99NOqDEzgPc48TkNFjh0oB+erkvkqnK9AUQxFgZfO1wKTI9bCoCsRDbDh1AZeWv0SG09vBCAiMILnOzzPs7c8S1iALGZaLFeOm1BEeYUGNcrX+QqyeHnsYr5HpVsZ7hRuWQph+Uvw95fy7Xrt5fbYyNpuP29xlNza5OxCzmUVcjwtH60G2jWK9Wq/AoFAUNEQ81GBQCBQgf2/waLRjr6BKEffQD9/j6pCoMQOVCTnqyRJjF0+lvn75xOgC2DhPQtpEd/C7f2sO3yRQouNOtHBNK8d4fF4BGWTlZXFzMX/EhQa7tL2xvxcxv6njY9HJShv3BZf//33X/r160dBQQH5+fnExMSQlpZGSEgIcXFxYrJbgch3Ol/VFV8jgrwv3AoLVGIHyiHzVRRulUBxqRq9FV8tjlgLx/G1M2UnE1ZPYMkR2dEapA/iqZuf4oWOLxAb4prwd6n4Wj+2fJ2vUJT76knpVrqr4mvaEfj5QUjdK9/uNBa6TQCd9y71xCjZ+ZqWZ2bNwQsAtKwTVeKiiUAgEFR2xHxUIBAIvMRqgj8nwvbP5Nse9g1UZZTYAUMFEl9nbpnJe9veA2DOgDl0a9jNo/0s35cCiMiB8iIoNJzQiCh/D0PgR9xWo8aMGcMdd9xBZmYmwcHBbN26lVOnTtG2bVveeecdX4xR4CFKpqfama9BBq3TReqp+BrhENnyfBw7IElSkfNViK8ABDuOB2+dr/kO56teJ3HvL/fS5tM2LDmyBJ1Gx2NtH+PoU0eZ3nO6y8IrlBT2ofwzX6Gkc9Rd0vPkwq0aYaVkvu7+CT69VRZeQ2rA/b9Aj5dVEV4BokMMBDqO9V/+OQuIvFeBQFBxueGGG8jMzARg6tSpFBQUuPQ4MR8VCAQCL0g/Bl/0LBJeOz4DDy0VwuslWJyFWxUjduD7Pd/z3IrnAHin5zsMaT7Eo/2YrXZWHkgFoG+LWh7tQyCoang6J3UVt79Fdu7cybhx49Bqteh0OkwmE3Xr1mX69Om89NJLqg5O4B35DmHT3cb2stBoNM7SLTViBySltckHKH8wAQJ16r4PlZVgR/att5mvZ7LkP9inc47ww94fABjSfAgHRh1g9n9mUzvC/eXzxZ2veq2G2g4XZ3nidL6qHTtgLpCXdP06Aiz50KAzPL4RmvTwaryXotFonO7Xf09nASLvVSAQVFwOHDhAfn4+AK+88gp5eXkuPU7MRwUCgcBD9v4qGwGSd8l9A/f9DD2nelT0WtWxOTJf9Wo7XwvMbp8Drz6xmuELhwPwbLtnGdt+rMfj2HQsjVyjlbjwQNrUda+kSyCoqng6J3UVt61WBoMBrVYWb+Li4jh9+jRNmzYlMjKSM2fOqDo4gXcUOJ2v6ouOkcF60vJMnscOOEQ2m12i0GIjRGV3roJStgWicEtBea8LPXS+ZhRm8ObGN/ls01aieAEJI32b9OX1216nTYJ32TTFC7fqRAerdpXZHRIvKaxyFUmSrh47cOGgHDNw8QCggVv/C7e+AFrfXBBIiAziRJr8hyPIoOWG+lE+eR6BQCDwltatW/PQQw/RqVMnJEninXfeISzsymWHkydPdv6/mI8KBAKBm1gKYdl42PGVfFulvoGqjNVxLqn30HB0Kco5gtlqJ99sc0bxlcXu1N0M/HEgFruFwUmDmdF7hldRAcv2yJEDvZvVKtHdIRBUZzydk7qK24pXmzZt+Ouvv7jmmmu49dZbmTx5MmlpaXzzzTc0b97c7QEIfIezcMvFL3V3cDpfPVzKHxqgQ6sBuwR5RqvvxFdrkfgqCrdklMxXd52veeY83tv6HtM3TyfHlEOorSsAN9Ruxh9Dx6kytuLOV3/kvYLnztd8s815vMWGFRNf/50HS54DSwGExsGgz6HRraqN90okRBY5hm9qEEOgXri+BQJBxeTrr7/m5ZdfZvHixWg0GpYuXYpef/mcQKPRlJjoivmoQCAQuEGJvgENdB4HXcerFntVVbHalcItdc4jQwL0BBm0GC12MvLMLomvp7NP03deX3JMOXSp34W5A+ei1Xg+HqvNzgolcqC5iBwQCBQ8nZO6itvftm+88Qa5ubkAvP766wwbNownnniCa665hi+//NLtAQh8R76PMl8BZ3mPp+HjGo2GsEA9OUYrOUYrcT4qWDRZHbmkWo24qudAiaFwNfPVZDXx2Y7PeG3Da1zIdxQ4xbekX+JzfL8ZEiPUW9Ju0GmdExJ/5L1CUeZrer4Zo8VGkME14VLJew026OSLCaY8WXTd9b28QaOucNf/ICzOF8MuQWJUkPP/Rd6rQCCoyFx33XX88IMcXaPValm1ahVxcWV/T4r5qEAgELjIrh9h8Rg59iqkBgz6HzS+zd+jqhQ4C7dUcr4CxIYGci6rkIwCM/XKON/JLMyk77y+nM89T7OazVh4z0KC9EGlPqYstp/MICPfTHSIgZsbxni1L4GgKuHpnNRV3FblbrzxRuf/x8XFsWzZMtUGI1AXp/PVJ7EDSuar51fdwoMM5Bit5Botag3rMsyibOsyXHW+2uw25u2Zx+Q1kzmVfQqAxtGNmdptKkOaD+HLjSeBA6ofX+FBBowWE/X85HyNDDY4BeALOaYyJ0UKJSIHUvfJ7oK0w6DRQreXoNNYn8UMXEpx56vIexUIBJUFu91e9kYOxHxUIBAIysBcAEufh3+/lW836CyvwAoXbkdXsdoU56t64mt0qEEWX/NNpW5ntBrp/0N/9l/cT+3w2iwdupTo4KJ8VrtdYsvxdLfPpRf8ew6Anknxfol4EwgqA+7MSV1FrDOowhQ42uh9Ib5Gh8jLql11BV4JZYl5nqMYzBco4mugEF+dKMdDofnK77skSSw6tIiJqyey7+I+ABLCEph862QeafMIBkcYv+KcVTsyIirYwMVck9+crxqNhoTIYE6k5ZOcXeiy+JqRZwYkhujXwP8+A6sRwhPkLK0GHX076EuoHS2Lr9EhBpISfGQrFwgEAh9w7NgxZs2axYEDBwBISkrimWeeoXHjxn4emUAgEFQiLusbeEHuHCgnI0BVQYkdMKgUOwAQExoIQEb+1UVTu2TngQUPsOH0BiICI1g6dCl1I+uW2OaXf87y/PzdHo+jb/MEjx8rEFQH1J6Tuq2aNGzYsNRw5+PHj3s0EIH6OAu3fJD5es9NdbmYa2JAG88D2hXxNdfoO/HVJJyvlxFUivN1zYk1jF81nm3ntgEQHRTNCx1f4Kl2TxFiKClC5vvIWT36tiasO3SRTtf4z7FZK0IurErJcT33NTs7g/cMH9E/b7N8R5MeMPBTCC3/19GxcSz331KPWxrFirgNgUBQaVi+fDl33nknrVu3pmNH+aLVpk2baNasGb///js9e/Z0bivmowKBQHAV/p0Hf4wDayGExcuxVz7uG6iqWFQu3AKICZGNLFdzvkqSxJhlY5i/fz4BugAW3rOQFvEtLttuxX45t7VBbAg1wgLdGkOTuDA6+/FcSyCo6LgzJ3UVt1W5Z599tsRti8XCv//+y7Jly3j++efdHoDAdyjiWLAPnK9NEyL4aOgNXu1Dabb3ZeyAEF8vJ+QKma9/n/+bl1a9xIrjK+RtDCE82+5Znu/4PFFBUVfcT6EzU1jd46t/69r0b+3f1lUl9/V8lovia/Iuuq8fSpTuDDZ06HpMgg7PgIpXyd1Br9Py2oDLJ2kCgUBQkXnxxRcZM2YMb7755mX3v/DCCyUmumI+KhAIBJdwWd9AN7jrs3LpG6iq2Ozqxw4ozlclsuxSZmyZwfvb3wdgzoA5dGvY7bJtrDY7W46lA/D+vW1oWSdKtfEJBAL35qSu4rb4+swzz1zx/o8++oi///7b7QEIfIMkSUXOVx8UbqmB0u7oS+erM/NV5Nk4UcR4o8XGwbSDTFw9kV8O/AKAQWvgsbaPMaHLBGqFlZ4Hle+ItQiuoMeXN9RyiK8p2YWlbyhJ8NfnsHwCUTYT56RYViZNY3ine8phlAKBQFC1OHDgAD/99NNl9z/88MPMmjWrxH1iPioQCATFuGLfwDi/GQGqCkrmqzc9J5cSEyobkDKvIL5+v+d7nl8hX0B8p+c7DGk+5Ir72H0um1yTlchgA80SI1Ubm0AgkHFnTuoqqn2L9O3bl19++UWt3Qm8xGyzO6/UhQRWzGyf8ogdMNuUzNeK+R74A6Vwa9uZnTT7uBm/HPgFDRoeaPkAh0Yf4oN+H5QpvAIUWuTPLbSCHl/eoDhfk7NLcb4as+Hn4bLDwGZib1gHbje9gbHWjVd/jEAgEAiuSs2aNdm5c+dl9+/cudPltlkxHxUIBNUKSYIdX8P/bpOF1/BEePAP6PK8EF5VwOpD52vGJeLrmhNrGL5wOADPtnuWse3HXnUfG4+kAdChcayqYxMIBDJqzEkvRbVv5Pnz5xMTE6PW7gReopRtAYR4UYrlS4piB8rB+SpiBwC4mH+Rn/bLjafnci5il+z0v64/u5/YzdyBc2kY3dDlfTmdrxX0+PKGWpFyYdVVM1/P/QOfdoH9i0Crh16vMz16ClmEExMaUI4jFQgEgqrDiBEjGDlyJG+99RYbNmxgw4YNvPnmmzz22GOMGDHCpX2I+ahAIKg2GHPgl0fg92fkotcmPeHxjVC/g79HVmWwOhrPDWpmvjrOFYqLr7tTdzPgxwFY7BYGJw1mRu8Zpeaabzwqi6/+7MgQCDzBZrMxadIkGjZsSHBwMI0bN+bVV19FkiTnNpIkMXnyZBISEggODqZHjx4cOXKkxH4yMjIYOnQoERERREVF8cgjj5CXl6faONWYk16K2+uF27RpU+KLQJIkUlJSuHjxIh9//LFHgxCoj5L3GqDXoq+gS+4V52ueyZeZr7JAWN3F1xxTDjO3zGTGlhnYCq8njpZEBNRk4SNbuKXOLR7ts9CHhW7+5qrOV0mCbbPhz0lgt0BkPRj8FdS5kYwdGwCIDRPiq0AgEHjCpEmTCA8PZ8aMGYwfPx6AxMREpkyZwtNPP11iWzEfFQgE1ZrkXXLMQMZx0Oigx8vQ/inhdlUZJXZAr+L7eqn4ejr7NH3n9SXHlEOX+l2YO3AuWs3Vny/fZOXf05kAdGoixFdB5eKtt97ik08+Yc6cOTRr1oy///6bhx56iMjISOdcb/r06bz//vvMmTOHhg0bMmnSJHr37s3+/fsJCpLP04cOHUpycjIrVqzAYrHw0EMPMXLkSL777jtVxunOnNRV3FZN+vfvX2Kyq9VqqVmzJl27duX666/3aBAC9fFVGZKalEvsgFWJHaieExGj1cjHf33MGxveIL1QDmVvEVufnGSoH9HEY+EVfFvo5m+UzNe0PBNmq10W7wszYdFoOLhY3uj6/0D/DyE4GoD0PHkCFRvqXtuoQCAQCGQ0Gg1jxoxhzJgx5ObmAhAeHn7FbcV8VCAQVEucfQMvgc0MEXVkI0Ddm/09siqJ4nzVqxo7UCS+ZhZm0ndeX87nnqdZzWYsvGchQfqgUh+//UQGFptE3Zhg6seGqjYugcAbcnNzycnJcd4ODAwkMPDy8+LNmzfTv39/br/9dgAaNGjA999/z/bt2wH5YvqsWbOYOHEi/fv3B2Du3LnEx8ezcOFChgwZwoEDB1i2bBl//fUXN94oR/598MEH9OvXj3feeYfExESvX487c1JXcVt8nTJlildPKCgf8h3ia0gFLkMS4qvvsNqtzNk5hynrpnA25ywA18Vex2u3vUbjsO4M/Hizs5DNUworeKGbN8SEBBCg02K22bmQa6RO/n74+SHIPg26AOj1Otw8Ahwn/pIkORtLReyAQCAQeE9ZE1wxHxUIBNUOYzb89pQcewVwXT/o/xGEiKgVX2FRnK8+iB3IMVq58/uB7L+4n9rhtVk6dCnRDlNHaWxw5L0K12v5Y7fbycrKcusxUVFRPhlLRSMpKanE7ZdffvmKc7UOHTrw2WefcfjwYa699lp27drFxo0bmTlzJgAnTpwgJSWFHj16OB8TGRlJu3bt2LJlC0OGDGHLli1ERUU5hVeAHj16oNVq2bZtGwMHDlT1tXkruiq4rZrodDqSk5MvC5lNT08nLi4Om807QUegDgUmWdAMqcCuxLBAR+aryfeFW9UldsAu2fll/y9MWjOJQ+mHAKgTUYdXur7CsFbD0Gv1HEqRr9wYLd79rirO14p8jHmKVqshPjKQsxn5SJs+gH+mg90K0Q1ld0FimxLb55ttTqFfxA4IBAKB7xHzUYFAUK04t0M2AmSdAq0Ber4CtzzpNAIIfIPNWbil3rlkZLABrQbsEmw5vZuIoAiWDl1K3ci6Lj1+k5L32qSmamMSuEZWVhYzF/9LUKhrYpwxP5ex/2lT9oZVgP3791O7dm3n7Su5XgFefPFFcnJyuP7669HpdNhsNl5//XWGDh0KQEpKCgDx8fElHhcfH+/8WUpKymXzP71eT0xMjHObiojb4mvxINzimEwmAgKE6FBRUFyNIRU4j7PI+eq7zFdn4VYFzb1VC0mS+PPYn7y0+iX+Sf4HgBohNXip00s8cdMTJZavKGKpt85X5zFWBcVXgGvCLUzJnUHdv/+V72g2EO54D4IiL9s2Pc8EyOVjFdltLhAIBFUFMR8VCATVgkv7BqLqwd1fQ522/h5ZtcBqU79wS6sBvd6M2RJAgCaGhff8jxbxLVx67IVcI4dSc9FooEPjWNXGJHCdoNBwQiOi/D2MCkd4eDgRERFlbvfTTz8xb948vvvuO5o1a8bOnTt59tlnSUxMZPjw4eUwUv/hskrw/vvvA3L2weeff05YWJjzZzabjfXr14uMrQqE4kqs7pmvJmvVd75uPbuV8avGs/bkWgDCA8IZ134cY9qPISLw8i/AIIN8TBRabEiSVGqT5tWQJKmY+FoFxcZTW5iRPopo3UWs2gD0fd+EGx++qrtARA4IBAJB+SDmowKBoNpQkCH3DRz6Q77d9A6480MIjvLrsKoTVqfzVT3xdcaWGeRZQwmgHi91nEa3ht1cfqziem2eGEm0OO8QVEKef/55XnzxRYYMGQJAixYtOHXqFNOmTWP48OHUqlULgNTUVBISEpyPS01NpXXr1gDUqlWLCxculNiv1WolIyPD+fiKiMuqybvvvgvIosvs2bPR6YpEvYCAABo0aMDs2bPVH6HAIyqDKzHcETuQJ8RXj9h7YS8TVk/gt0O/ARCoC+TJm55kfKfx1Ay9+jKU4seE0WL3qDDLbLM7l+GEBFbcY8xt7HbY9C6sfp1oycYxewIrm77FYzf1L/VhGUrZlogcEAgEAo+wWCz06dOH2bNnc80111x1OzEfFQgE1YIzf8H8hyD7zBX7BgTlgyK+GlRaRfn9nu95fsXzxGumgQSt4zq69fiNR+QC5Y4i71VQSSkoKEB7SYyHTqfD7ii3a9iwIbVq1WLVqlVOsTUnJ4dt27bxxBNPANC+fXuysrLYsWMHbdvKqwBWr16N3W6nXbt2Xo/R1Tmpu7gsvp44cQKAbt268euvvxIdXXYYtMB/5DszXyuuK1FxvhZabFhsdtX+qBWnqHCr6giEJzJP8PLal/l297dISGg1Wh5q/RAv3/qyS1lBivMVoMBs9Uh8LSwWWRBiqCLvbd5FWPAYHFsFwLFa/bjz5CButdYp86EZDudrrLgCLRAIBB5hMBjYvXt3mduJ+ahAIKjS2O2w5UNY9UqxvoGvIbG1v0dWLbEqhVsqOF9Xn1jN8IXysupGMfGcTys6h3AFSZLYePQiAJ2vEeKroHJyxx138Prrr1OvXj2aNWvGv//+y8yZM3n44YcBeWXTs88+y2uvvcY111xDw4YNmTRpEomJiQwYMACApk2b0qdPH0aMGMHs2bOxWCyMHj2aIUOGkJiY6PUYXZ2TuovbytyaNWtUH4RAfZxN9BXYlRgWVHT45RmtPlk6Ya5CzteUvBReW/8an+34DItdzskdnDSYV7u9ynU1rnN5PzqthkC9FpPVTqGHpVv5juMrQK9FXxXydE9uhPmPQF4K6IOh33SOGHqSf/IfkrONZT48LV/OfI0JvXKwuEAgEAjK5v777+eLL77gzTffLHNbMR8VCARVjvx0WPgEHFku3252l6NvoOwcRYFvsDrceN6Kr7tTdzPwx4FY7Bb+r9n/0Ujblu/TzpCe57r4euxiHqk5JgL1WtrWFxceBZWTDz74gEmTJvHkk09y4cIFEhMTeeyxx5g8ebJzm//+97/k5+czcuRIsrKy6NSpE8uWLSMoqKjHZt68eYwePZru3buj1WoZNGiQM5pKDdyZk7qK2+LroEGDuPnmm3nhhRdK3D99+nT++usvfv75Z9UGJ/AcRRwLNlRc56tBpyXIoMVosZPrI/HVZHWIhJVYIMwyZjF903Te2/YeBZYCAHo17sUbt71B20TPwvaDA3Sy+Oph6VahWXFWV1xx3yXsNlj/Dqx7EyQ71LhOdhfEJ5FwJguA5KyyxVcROyAQCATeY7Va+fLLL1m5ciVt27YlNDS0xM9nzpzp/H8xHxUIBFWKU1vgl0cg5xzoAqHvW9D2QREz4GcsivPVi3PJ09mn6TuvLzmmHLrU78KcAXP4cNUpADILXBdfNxyR815vahBTYiWjQFCZCA8PZ9asWcyaNeuq22g0GqZOncrUqVOvuk1MTAzfffedD0Yo486c1FXcVubWr1/PlClTLru/b9++zJgxw+0BCHxDgVK4VYGdrwDhQQaMFhO5JotP9l+Zna8FlgI+2PYBb216i0xjJgC31LmFad2n0bVBV6/2HWLQkYXFc+eryebcT6UlNxV+HQEn1sm3Ww+Ffm9DgPzFmhApX1m7kGvEarOXOukSsQMCgUDgPXv37uWGG24A4PDhwyV+dmk5pJiPCgSCKkGxvgEkG8Q2gcFzoFZzf49MANgczldPC7cyCzPp820fzueep1nNZiy8ZyFB+iBnSW+6G7EDStlWJxE5IBD4HHfmpK7itvial5dHQMDlAoPBYCAnJ8ejQQjUp7I00YcH6bmYayLXR6VbZpuS+Vp5xFeLzcLn/3zOq+tfJTkvGYBmNZvx+m2vc+d1d3r8y16cIIdjtcBD56vz+Aqs2MfXVTm+Fn4ZAfkXwBACt8+E1veW2CQ2LBC9VoPVLnExz0RCZPBVd5fmmDjFCPFVIBAIPMadKAExHxUIBJWevIuwYCQcWy3fbnmPPCcNDPPvuAROlMxXg8798y+j1Uj/H/pzIO0AtcNrs3ToUqKD5bgA5Zwh00Xx1WKzs/V4BgCdRNmWQOBzfBFv5bYi1aJFC3788cfL7v/hhx9ISkpSZVAC7ymoJMvCwx3inc/EV2vlEV/tkp15u+dx/UfX8+SSJ0nOS6ZBVAPmDpjLrsd30f/6/qoIr1B0XHjqfK0sx9dl2Kyys2DuAFl4jUuCkWsvE15BvsIdHyG7X8vKfc1wZL6K2AGBQCDwnqNHj7J8+XIKCwsBuWTkUsR8VCAQVGpObIDZnWThVR8Md34IAz8VwmsFw2qX//7otO6dS9olOw8seIANpzcQERjB0qFLSxQjK+Krq4Vbu85kkWeyEh1iIClBZAALBOWFK3NSV3HbtjZp0iTuuusujh07xm233QbAqlWr+P7770W+VgXCuSy8gotj4UEGAPJ8FDtgqgSxA5Ik8ceRP5iwegK7U+VWvfjQeCZ2mcjItiMJ0Kkv6AU74gI8zXwtclZX7OOrBDnJcpbWqU3y7RuGy3lahqs7WmtFBnEuq5CUssTXPMX5Kgq3BAKBwFPS09P5v//7P9asWYNGo+HIkSM0atSIRx55hOjo6BJxAmI+KhAIKiWX9g3UvF7uG4hr6u+RCa6AUrjljvNVkiTGLBvD/P3zCdAFsPCehbSIb1FiG3fF142OyIEOTWqg9bL8SyAQlI07c1JXcVuRuuOOO1i4cCFHjx7lySefZNy4cZw9e5aVK1cyYMAAtwcg8A2KqBZawZeFhweVj/O1ooqv60+tp/NXnbnj+zvYnbqbyMBIXr/tdY49fYzRN4/2ifAKEOyIo/BcfFWcrxX7+HJyZCXM7igLrwFhMOgLuPP9UoVXkMVXKN35KkmSM3ZAZL4KBAKB54wZMwaDwcDp06cJCQlx3n/PPfewbNmyEtuK+ahAIKh05KbCNwNg7Ruy8Nr6fhixWgivFRgldkDvhvN1xpYZvL9dbl2fM2AO3Rp2u2wbZ+xAgdklJ91GR9lWZxE5IBCUC+7MSV3FI+Xk9v9n777jm6q7B45/stp0lzJaloCIbEFBAZElyHKwFPDBAfK4HlChj4A4WCooAiqKoigIj6D+QKmKgiKIDEEQWcpQtggto5TO7Pv74yZpC91NmtHzfr146U3u+Ca5Tb45Ofec22/n9ttvv+L233//nRYtpDi4P8gKkMvCIyus7IB/PQ+7zuziufXPsfrwagCMeiNP3vQkE26ZQFxYnNePH2ZQJxDZZS47ECCZr3Yr/PgybH5dXU5oCXd/BNWuKdHmNZ1lB5Iv5RS6TpbF7j7PpOyAEEKU3ffff893331HnTp18t3eqFEjTpw4ccX6Mh8VQgSMIz+qjV6zzoEhAu6YA62G+npUohiusgP6EmabLtu3jHFrxwEwu+dshrYo+DV2BV+tdoV0k42YMEOh+8wwWdn1dxoAHSX4KkSFKO2ctCTKnbaWkZHBJ598wgcffMDOnTux28sWzBGeFTgNt9QPGm8FX83OhlshRXSqr0h/XfiLF358gc/+UOvU6bV6/n39v3mhywvUiqpVYeNwnRemYC47cOkUrHgI/v5FXb7x39DzZTAYS7yLkmS+ukoOGA1av/97E0IIf5aVlZUvu8AlNTWV0NCiy7rIfFQI4ZfsNrXEwMZZgAI1mqtlBqpf6+uRiRKwOr9L6ktQdmD9sfUMTxoOwJh2Y0jskFjoukaDjvAQHdkWOxezLEUGX385mordoVC/ajh14678jBRCeF555qSFKXNEauPGjTzwwAPUrFmTWbNmceutt7Jt27ay7k54WKA0RMotO+Clmq/OzE5flx04lX6KR75+hKbzmroDr/e2uJcDow7w7h3vVmjgFdQPfMgNopaW35cdOLRGbWLw9y8QGq1Ocm+fXarAK0CtWLUsQVE1X8+7mm1JvVchhCiXTp06sWTJEveyRqPB4XAwc+ZMunW78rJNkPmoEMKPpZ+GJXfBxtcABdoMh4fXSeA1gNjdDbeKDr7uTdnLgM8GYHVYGdx8MLN7FV8P0pX9eqGYuq+ueq+S9SpExSnLnLQ4pYqcJCcn89FHH/Hhhx+Snp7O4MGDMZvNJCUlSWdZP5NtlpqvABa7b2u+Xsi+wCubX+HtHW9jsqkBvNsb3c7Lt75Mq4RWPhkT5Ablc8pYdsBvG7rZLLBuKmx9W12u2RruWQRxV5dpd6XJfJWSA0IIUT4zZ86ke/fu/Prrr1gsFsaPH88ff/xBamoqW7Zsca8n81EhhN/76wdY+QhkX1D7Ddz5JrS829ejEqXkqvlqKOIqypOXTtJnaR/Szel0rteZxf0Xo9UU/92zakQIpy7mcLGEwddOjST4KkRFKemctDRKHJG68847ady4MXv37uWNN97g9OnTvPXWW2U6qPAuRVECpuarK/iaafZ2zdeKDb5mWjJ58acXuXru1czaOguTzcQtV93CphGbWPWvVT4NvAKEOTNfcyxle979sqHbxROwqE9u4LXd4zDy+zIHXgFqOoOvKekmHI6Ci+G7upTGSbMtIYQolxYtWvDnn39yyy230K9fP7Kyshg4cCC7du2iYcOGgMxHhRB+zm6FtZNh6SA18JrQEh7dKIHXAGVzqN8lC8t8vZhzkd4f9+Z0xmmaV29O0pAkjPqSXWlXxfndIbWI4GvyJROHz2ai0UCHqyX4KkRFKcmctLRKHDlZvXo1Tz75JI8//jiNGjUq08FExTDbHLjiRP4ffHXVfPVO2QFX8LWiMl/NNjPv7XyPlze9zNmsswC0im/F9O7T6XNNHzSakhVr97aw8ma+OoO2riCuzx1YBV/+B0yXwBgD/d6BpneUe7fVI0PRatRi++ezzNSIunIyJWUHhBDCc2JiYnjuuecKvV/mo0IIv3VFv4GHoedLpS57JfyHq+GWoYCaryabiX6f9uPA+QPUjqrN6mGrqRJWpcT7diVupGYXHnx1Zb1eVzuGmPDC68IKITyvuDlpaZU4IrV582YyMjJo06YN7dq14+233+b8+fMeG4jwnLx1PP22JqdTRZUd8Hbmq91h56PdH9H47cY8teYpzmadpWGVhiwbuIzfHv2Nvo36+k3gFXKDpmWt+Zqb+erj4KvNDKsnwGfD1MBr7bbw6CaPBF4B9DqtO+B6Jq3g0gNSdkAIEQg2btzInXfeSa1atdBoNCQlJeW7f/jw4Wg0mnz/evfunW+d1NRUhg0bRnR0NLGxsYwcOZLMzMx86+zdu5dOnTphNBqpW7cuM2fOLNU4L168yKxZsxg5ciQjR45k9uzZpKamuu+X+agQwi8dWn1Zv4HFcPssCbwGOKuz7IBem/+7pN1h5/6V97Pp5CaiQ6NZPWw1dWPqlmrfceHFZ75ucQZfb5GSA0JUuOLmpKVV4ohU+/btWbBgAWfOnOHRRx/l008/pVatWjgcDtauXUtGRkaZByE8K8t5CX+oXltscXBfiwz1bvDVbHVmvuq8EyRUFIWVB1bS8t2WjPhyBCcunaBWVC3m3z6fA6MOcG/Le0tU86eiuTKiTWXMfHUFbcN8GdxPPQof9oRf5qvLHUbDiNVQpZ5HD1Nc3VcpOyCECARZWVm0atWKefPmFbpO7969OXPmjPvfJ598ku/+YcOG8ccff7B27VpWrVrFxo0beeSRR9z3p6en07NnT+rVq8fOnTt57bXXmDJlCu+//36Jxrhx40bq16/P3LlzuXjxIhcvXmTu3Lk0aNCAjRs3AjIfFUL4GZsFvnsOPhkKOReh1vVqmYHm/X09MuEBdmfZAX2e79SKopD4XSIr9q8gRBdC0pAkWsa3LPW+45yJGxcyCw6+KooizbaE8JGSzElLq9SRk4iICB566CEeeughDh06xIcffsgrr7zCM888w2233cZXX31VpoEIz8n2x3qchfB62QEvNtxad3Qdz65/lu3/bAegirEKE2+ZyOibRhNmCPP48TzJVXagrJmv2c6yAxG+Kmvxx0r46kkwp0NYFeg/Hxr3Ln67MqgZY2T335B8KafA+10dSqtK8FUI4QMZGRmkp6e7l0NDQwkNvbIMSp8+fejTp0+R+woNDSUhIaHA+w4cOMCaNWvYsWMHbdu2BeCtt96ib9++zJo1i1q1arF06VIsFgsLFy4kJCSE5s2bs3v3bubMmZMvSFuYUaNGMWTIEN599110zh9N7XY7//nPfxg1ahT79u1zryvzUSGEz108rpYZ+Genutz+P9BjKuhlThgsXA239Hkabs3eOpu52+cCsLj/Yro1KFvnc1fm68VCyg78mZLJuQwzRoOWNvVKXs5ACFF+pZmTllS5IlKNGzdm5syZnDp16orsCOE72QHSbAsgOk/DLUUpuKFRWdkdCnZnnR5Plh3Y8c8OeizpQY//9WD7P9sJN4TzXKfnOPrUUcZ1HOf3gVfI03Cr3JmvFXyOWU2wKhGWD1cDr3Xbw2ObvRZ4hTyZr+kFZ75ecNV8lbIDQggfaNasGTExMe5/M2bMKPO+NmzYQI0aNWjcuDGPP/44Fy5ccN+3detWYmNj3YFXgB49eqDVavnll1/c63Tu3JmQkNz3w169enHo0CEuXrxY7PEPHz7Mf//7X/ckF0Cn05GYmMjhw4cL3U7mo0KICnfga5jfWQ28GmNg6DLoPUMCr0HGVfPVdTXpJ/s+YdzacQDM7jmboS2GlnnfrqvmLhRSdsCV9XpTg6qE6v3/e70QwaSsc9KieCQ1UqfT0b9/f/r37++J3Ylycme++nm9V4BIZ/DVoajj9mS2rqvZFngm83X/uf08v/55Vh5cCYBBa+Cxto/xXKfniI+ML/f+K5K74VaZM199cI6dP6wGXVOcvzLdkgjdngOdd8dQ0xl8TS6s7ECmq+yANNwSQlS8/fv3U7t2bfdyQVmvJdG7d28GDhxIgwYNOHLkCM8++yx9+vRh69at6HQ6kpOTqVGjRr5t9Ho9cXFxJCcnA5CcnEyDBg3yrRMfH+++r0qVojN3brjhBg4cOEDjxo3z3X7gwAFatWpV7GOQ+agQwutsZvj+Bdj+nrpc50a4eyHEXuXbcQmvsDmvojToNKw/tp4Hkx4EYEy7MSR2SCzXvl2JGxcLC77+dQ6ATlJyQIgKV945aUH8PzonSs1V87XCsxLLIMygQ6fVYHcoZJhsHg2+mm25gcXyBF9PpJ1gyk9TWLJnCQ7FgQYN97e6n6ldp1I/tr4HRlrxXFnRZc98reDs6r3LYdUYsGRCeDUY+B5c06NCDp0Qo2YyF1TzVVEUKTsghPCpqKgooqOjy72foUNzs3datmzJddddR8OGDdmwYQPdu3cv9/4Ls3fvXvf/P/nkkzz11FMcPnyY9u3bA7Bt2zbmzZvHK6+84rUxCCFEiaQeheUj4MxudfnmJ6H7JNBJF/pg5cp8PZL6F8O/HYDVYWVw88HM7jW73PuuUkTDLYvNwS/H1MY+Uu9ViIrh7TmpBF+DkCug5vNO9CWg0WiIMupJy7aSYbK6L/H2BFfmq0aTv0h6SZ3NOsvLG19m/s75WOzqh2L/Jv15qdtLNK/R3GPj9AWjoXw1X7Oc24V7u66wJRvWTIDflqjL9W6BQR9AdE3vHjePojJfsyx2zM7zTMoOCCGCydVXX021atU4fPgw3bt3JyEhgbNnz+Zbx2azkZqa6q4Tm5CQQEpKSr51XMuF1ZJt3bo1Go0mX+mh8ePHX7Hev/71L4YMGVKuxySEEGX2+xdqvwFLBoTFwYD5cG0vX49KeJkr+Dp6zeOkm9PpUq8Li/sv9khD5arOq+YyzTbMNnu+0gK7Tl4k22KnWmQITRKiyn0sIUTxvD0nleBrEMoyOwNjAVB2ACAy1Bl8dWbseoorKBaq16LRlDz4esl0idlbZzNn6xyyrFkAdKvfjRndZ9CuTjuPjtFXXOeGqQzBV5vd4Q5shxu8GOA/d0gtM3B2P6CBLuOh83ivlxm4XEJ0bvBVUZR855Kr5IDRoA2YvzchhCiJU6dOceHCBWrWVH/s6tChA2lpaezcuZM2bdoAsH79ehwOB+3atXOv89xzz2G1WjEY1EywtWvX0rhx40JLDhw7dqwCHo0QQpSR1QTfTYRfF6rLV3WAQR9CTO2itxNBweK8kvJs1hmaxzcnaWgSRr1nkoWijHr3FaAXs6wkxOR+r9rirPd6c8NqaMuQRCSEKD1vz0klWhCEAqnhFkCU0QDkkGHybPDV4qzRE6Ir2S+TOdYc5u2Yx4zNM0jNUS/zaFurLdNvnU6Pq3uUKoDr71wNt7Kt9isCisXJzlOqwGulLXYvg2/+C9ZsiKgBgxbA1V29c6xixDuDrxa7g9QsC1Ujc+spupttSb1XIYSfy8zMzNcg4NixY+zevZu4uDji4uKYOnUqgwYNIiEhgSNHjjB+/HiuueYaevVSM7uaNm1K7969efjhh5k/fz5Wq5XRo0czdOhQatWqBaiZAFOnTmXkyJFMmDCB33//nTfffJPXX3+90HHVq1fPuw9cCCHKKl+/AQ10SoSuz1Z4IoDwDZPNRJYlBwghPrI6q4d9Tawx1mP712o1VAkP4XymmQtZ5nxXgG5yBl9vaSQlB4SoKN6ek8onRxAKtMzXKGfTrQyT1aP7NVudwddiukPaHDYW7VrE1J+m8k/GPwA0qdaEl7q9xMCmA4Mq6OriCpraHQpWu0KIvuSP0dWkS6fVEOqBRmb5WLLgm6dhzzJ1uUEXGLgAonzX0CxEr6VaZCjnM82cuWTKH3x1Zr5KyQEhhL/79ddf6datm3s5MVFtFPLggw/y7rvvsnfvXhYvXkxaWhq1atWiZ8+evPjii/kaeC1dupTRo0fTvXt3tFotgwYNYu7cue77Y2Ji+P777xk1ahRt2rShWrVqTJo0iUceeaTE4zx9+jSbN2/m7NmzOByOfPc9+eSTZX34QghROnv/D74eA9YsZ7+B9+Ea79W/Fv7F7rBz/8r7cSjD0ABLBiyibkxdjx8nLsLA+UwzF7Nyvwenm6zs+TsNgFuk3qsQPuPpOWlgROdEqWRb1QzSiEDJfHXWDc30UuZrYQFCh+Jg+R/LeeHHF/gr9S8A6kbXZWrXqdzf6n702uD98wjLUy4gx2IvVUMyV0O3cIPOs4HplP2w/EE4/ydotNB1InT6L2h9fx7XijVyPtNM8iUTLWrHuG93FciPk2ZbQgg/17Vr13w1rC733XffFbuPuLg4li1bVuQ61113HZs2bSr1+AA++ugjHn30UUJCQqhatWq+zxiNRiPBVyGE91myYfV42PU/dbl+JzURoAL7DQjfUhSFxO8SWbF/BVdxPwAtajT1yrFc3yFcV9MBbDtyAYcCV1ePoFZsmFeOK4QomjfmpMEbXarEst2Zr74PWpVEbuarh4OvtoKDr4qisObwGp5b/xy7kncBUC28Gs91eo7H2j7msTo+/ixEr0Wv1WBzKORY7cRQ8i6t2e5mWx46vxRFbai1ejzYTBBVU22qVf8Wz+zfAxKijezlEmfS8zfduiDBVyGE8JgXXniBSZMmMXHiRLRaD19ZIYQQxTl7UC0zcO4Aar+BCWrPAT9IBBAVZ/bW2czdPhcUDRrU115fwjJ2peUqXXbR+Z0CYLOr5IBkvQrhM96Yk/rFzHbevHnUr18fo9FIu3bt2L59e4m2+/TTT9FoNPTv39+7AwwwWa6ar97uRO8has1Xz5cdcAVf82Z1/vz3z3Rd3JW+y/qyK3kXUSFRTO06laNPHmVM+zGVIvDq4q77aild0NsdfPVEWQtzBnzxMHz9pBp4vaYHPLbZrwKvADVjXE23cvLdfiFT/ZW6WqTUfBVCiPLKzs5m6NChPgu8ynxUiEps11JY0E0NvEbGwwNfQreJEnitZJbtW8a4teMAmHnbLPftep13ytBViVC/B6cWEHztKMFXIXzGG3NSnwdfP/vsMxITE5k8eTK//fYbrVq1olevXpw9e7bI7Y4fP87TTz9Np06dKmikgcNVkzNQyg5EOjNf0z2c+Wp2dqcM0WvZm7KXOz+5k44LO7LxxEZCdaEktk/k6FNHmdRlElGhUR49diBw1X3NydNAqyQ81dAtOvsE+oU9YN9y0OigxxT413KI8L+JRkKMesnPmbT8ma9SdkAIITxn5MiRLF++3CfHlvmoEJWTzm5C99Uo+PI/aqPXq7uqiQBXd/H10EQFW3d0HcOThgMwpt0YRt2Ye1mxXuud4GucM/PVdTXd6bQcjp7LQquBDg2reuWYQojieWNO6vPUyDlz5vDwww8zYsQIAObPn88333zDwoULeeaZZwrcxm63M2zYMKZOncqmTZtIS0urwBH7vyxPZiZWAFfZgUyzd8oOHE87TOv5D6GgoNPoGNF6BJO6TPJK0fRA4g6+WkobfC1nWQtFQbtzIZ3/nIZGsUJ0bbh7IVzVvmz7qwCuzNczl6TsgBBCeMuMGTO44447WLNmDS1btsRgyF8SZ86cOV47tsxHhaiEzu6ny6HJaM1n1H4D3Z6FWxIl27US2pO8h4H/NxCrw8rg5oOZ3Ws2Gabc70h6L12REReufs5dzFa/U7iyXlvVjSXaWPKycEIIz/LGnNSn0TmLxcLOnTuZOHGi+zatVkuPHj3YunVrodtNmzaNGjVqMHLkyGKbOpjNZszm3ALWGRkZAFitVqxWz17m7i+ynJfvh+gIiMcYblA/zC5lW0o0Xtc6Ra17JvMM83csBm4gJfsflFCFu5vezeTOk2lctXGx21cGYc5yDBk5JXveXTJy1L+nMIO29M+hKR3dt2PRHfgSAHvD23DcNQ/C48CPX49qEepb5ZlLOfke8/lMNRgba9RVqvOpJH+Dwr/Ja1g0q9WKothxOIr/cUpR7O45RVm3K+sYg82MGTP47rvvaNxY/Zy+vLmBt1TEfBQq55w0mMn7aABTFDS7P0b//USibCYckQk4BryPctXNYHeo/0RA8MTf4clLJ+m7tC/p5nQ6X9WZD27/ALvNjsmcWwpAsduwKp7/HIoxqoH+8xlmrFYrGw+pV1vcfHVcpXlvCaT30tLM8yB3ruf6/4rariLnpIHwupWFN+akPg2+nj9/HrvdTnx8fL7b4+PjOXjwYIHbbN68mQ8//JDdu3eX6BgzZsxg6tSpV9y+ceNG9u/fX+oxB4Lk8zpAwx97fsNxovDOxv7iyDkNoOP4P8l8++23Jd5u7dq1V9yWactk5dmVfH3uawzWzlTjBqL1YUy4djYNQxty5JcjHOGIB0cfuExZ6nmyedt20v8s+XmyI1l9vS5dOFeq1ys2+yhtj71DhOUsDnTsrz2YI1G9YcO20g++gp03Aej552IW33zzLa7323+cf2sHd+8gpxKeVgX9DYrAIq9hwTIyMjjyjxZjRPElaUxZGaw1HSEqKqrM25XF+fPny7SdP5s9ezYLFy5k+PDhFXrcipiPQuWck1YG8j4aWPT2HFr9vYg6F9X5Z0rUdfxW7xEsv6fB7yWf1wr/Uta/wwxbBhP/mshp82muMl7FI9GPsP779QBcsgDo0aCwZs1qzw02j7/S1O9VJ1NSWfXNt2w4oH630J77k2+//dMrx/RXgfBeWpp5HuTO9YAK3a4i56TBOB8F78xJA+O6dKeMjAzuv/9+FixYQLVqJasLOXHiRBITE93L//zzD82aNaNz587Ur1/fSyP1rTmHNkN2Nl07tqdNvSq+Hk6xjIfO8b/DuzBGxdK3b/GXnlutVtauXcttt93mTv/OsmTx9q9vM3vbbNJMaQA0jr2W9HPQtWEnnri7tRcfQWD6LOVXjmem0qxla/q2qlni7U5tOgbH/uLqenXo27dF8RsoCtpfF6D94WU0DitKTF0sd87nyB8X8r2G/sxstfPirnVYHRo6druN2HADiqIwfsc6wMEdPbtSt0q4r4dZYQr6GxSBRV7DoqWmpnJs01HCo2KLXTc7I43bOl1NXFxcmbcri+PHj5dpO38WGhpKx44dfT2MYpVlPgqVc04azOR9NAAl70O/ciSai0dRNDqsnZ9h26VG3Nazl7yGAao8f4cmm4m+n/TllPkUtaNq8+ODP1I3Orcs3ZlLJti5Eb1OS9++vTw9dAAanMngnQNbsWpDaXhDGzK3bSU8RMdjd/fI1zQ6mAXSe2lp5nmQO9cDKnS7ipyTBuN8FLwzJ/Vp8LVatWrodDpSUlLy3Z6SkkJCQsIV6x85coTjx49z5513um9zONTLQvR6PYcOHaJhw4b5tgkNDSU0NLcTeXp6OgAGg8Hv/7jLKtvZQCkqPDQgHmOVCLWeZqbZXqrxGgwGFK3Cgp0LeGnTSyRnJgPQokYLXr71Zc6dbcGL3xzAGKIPiOehooWHqn/+Fgelen7MzisXIkNL8DeUcxG+HA0HV6nLTe5A0+9tdPpI+OPbgPk7NBgMxEWEkJpl4Xy2jeox4WSZbZiddYUTYiMwGALqtyyPCJTXTxROXsOCGQwGNBod2hLU/dNodO7nsazblXWMweapp57irbfeYu7cuRV63IqYj0LlnJNWBvL6BQBFgV8/hDXPgt0M0XXQ3L0QTc0b4NvAmY+KwpX2NbQ77DyU9BCb/95MdGg0q4et5uqqV+dfSaNeTm3Qab12fsTHqskbaTlWth67CEC7BnFEhIUWtVlQCoS/w9LM8yB3ruf6/4rariLnpP7+mpWVN+akPo0WhISE0KZNG9atW0f//v0BdfK6bt06Ro8efcX6TZo0Yd++fflue/7558nIyODNN9+kbt3K3UDJxdVAKSJAGm5FOoOAGaaS1wuxK3aW/r6UaRuncSztGAANYhswrds07m1xLzqtjnfPqKn6IbrK8athaYU5z49SN9xyNkYLDy3mjfzUr7B8BFw6CVoD9HwJ2j0KGo1f13ctTEK0kdQsC8mXTDStGc2FTLUOlNGgDZjmdkII4c+2b9/O+vXrWbVqFc2bN79iQv/FF1945bgyHxUiiJkuwVdPwv4kdfnaPtD/Hb/vNyC8R1EUEr9LZMX+FYToQkgakkTL+JZXrGdz/aim9V7N8Vhnwy27Q+Hb39VEolsaVffa8YQQJeONOanPIwaJiYk8+OCDtG3blptuuok33niDrKwsd7fZBx54gNq1azNjxgyMRiMtWuS/zDk2NhbgitsrK0VRyLKUMDjmJ6KMruCrrdh1FUXh6z+/ZuyhsZzccxKA+Ih4Xuj8Ag+3eZgQXW7XeYszKzHUIMHXgoQ5n5ccaymDr871wwvL9FQU2Po2/DAFHDaoUh/uXgS1byjHaH2vZoyR/WfS1UuQgAtZatOUqhGV75dpIQKFw+EoVQf62NhYtF7qaCyKFxsby8CBA31ybJmPChGE/vkNVoyAi8dBq4fbpkH7/4AXG/gJ/zd762zmblez2Rb3X0y3Bt0KXM/mUHti6L2YyBOq1xEVqifDbGPP32kA3HJNycvZCCG8wxtzUp8HX4cMGcK5c+eYNGkSycnJtG7dmjVr1ribHpw8eVK+CJWCyepAcfZOCpRsvGij+iuC2ebAYnMUWt/mp+M/MXHdRLaeUjsPx4TGMKHjBJ5s9yQRIRFXrG+xq0FCyXwtmOv8yLYUH/TOy5X5GlFQcD87FZIehz/XqMvN+sNdc8EYU56h+oWEGLU8RvKlHABSs9TM16qRIYVuI4TwrbS0NOas2lXiZgOJd1xf5hqsovwWLVrks2PLfFSIIKIo8Mt78P3z4LBC7FVw90dQp42vRyZ8bNm+ZYxbOw6A2T1nM7TF0ELXtdq9n/kKUCUihAzn96vqUaFcGx/p1eMJIYrnjTmpX0TnRo8eXeBlXQAbNmwoctuPPvrI8wMKYFl5AmlhhsDIfM0bxMswWakamT+T8Lczv/Hsumf57sh3AITpw+gT14d3hr1DfHT+zsR5ma3OzNdKUqy8tMJC1Oc9x+Io1XbZzjIFru3dTm6DFSMh/RToQqH3dGg7MmiyC2o6g6/uzFdn2YG4CAm+CuHPjBFRRETH+noYIgDIfFSIIFBAvwH6zYOwWJ8OS/jeuqPrGJ40HIAx7caQ2CGxyPXtrsxXLwdf4yJCOJmaDahZr5og+e4khMjPL4KvwnNc9TvDDDp0Xv6g8BS9Tkt4iI5si51Ms80dfD10/hAv/PgCy/cvV9fT6nn4hod55uZn2LVxF3FhRWcnWZy/VlaWTpGl5QrO51hLmfl6eU1hhwO2vAHrXwLFDnEN4Z6PoOZ1Hhyt79WMCQMgOd1VdkCCr0II4UkNGjQo8kvn0aNHK3A0QoiAk7ffgC4Eer4MNz0cNIkAouz2JO9h4P8NxOqwMrj5YGb3ml3sNla798sOAFTN812io5QcEMIveGNOKsHXIOOu93p5VqKfizLqybbYyTDZOJV+iqkbprJo9yLsih0NGu5teS/Tuk6jYVxDrFYru9hV7D7dNV8l+FqgcHfmaylrvjrPsbAQHWSdh5WPwuEf1Dtb3gN3vA6hxV/iG2guz3xNddZ8rRYpNV+FEMITxowZk2/ZarWya9cu1qxZw7hx43wzKCGE/3M4YNu8PP0GGsA9i6DW9b4emfADJy+dpO+yvqSb0+lSrwuL+y9Gqyn++2FFZb5WyRN8lXqvQvgHb8xJJfgaZLLMzmZIAdJsyyXKaCAl3cyrm+ay/PDLmO1qYOuOa+/g5Vtf5rr40mdRuoKvkvlaMKMz8zW71MFXdf2aF3fCmv9CxhnQG6Hva3D9/UGbXZBb81XKDgghhDc89dRTBd4+b948fv311woejRAiIGSnwsrH4C+1PBnNB8CdbwZFvwFRfqk5qfT+uDenM07TvHpzkoYmYdQbS7StzVXzVefd7zauzNdrakS6v28IIXzLG3NSiUoFmZzLLwkPABnmDC6ZkwH4fP83mO1mOtfrzOYRm/n63q/LFHgFtYEXSMOtwrgzX62lC76azBae0H1By3X3qYHXatfCwz/CDQ8EbeAVcoOvmWYb6SarlB0QQogK0qdPHz7//HNfD0MI4W9OboP5t6iBV10o3D4H7l4kgVcBgMlmov+n/Tlw/gC1o2qzethqYo2xJd7e5s589e53yevqxAJwV6taXj2OEKL8yjMnDZwInSiRQCo7YLKZmP/rfKZvmo4m4wnCuIEG0c2Y3X8KvRr2KnexcXfwVe//z4UvuGu+libzNSOFV01TaGfYBwrQ6l9w+ywIifDOIP1IeIiemDADl3KsJF8ykeoMvlaLlOCrEEJ404oVK4iLK7rOuxCiErm830DVa9R+AwktfT0y4SfsDjv3r7yfTSc3ER0azephq6kbU7dU+7A5KibztW/LBNb/twv1qwb/9ykhAl155qQSfA0y2e7gq/++tDaHjSV7ljBlwxT+Tv8bgAahWhw58HSH5+l9zdUeOY6r4ZbUfC1YWGkzX49ugM8fpp1ylmwllJzbZlL1luFeG58/qhlj5FKOlTOXTFzIVEtjxEVIzVchhPCE66+/Pt8Pr4qikJyczLlz53jnnXd8ODIhhN/IPKf2GziyTl1uORjumBOU/QZE2SiKQuJ3iazYv4IQXQhJQ5JoGV/6wLy74ZaXa75qNBqurh7p1WMI4U/++ecfJkyYwOrVq8nOzuaaa65h0aJFtG3bFlD/hidPnsyCBQtIS0ujY8eOvPvuuzRq1Mi9j9TUVJ544gm+/vprtFotgwYN4s033yQy0jN/S96Yk/pvhE6Uiasepz9mviqKwhcHvuD5H5/n4PmDANSOqs3kLpP58+iNLN/5j7tmrSdYbOq+pOZrwUqc+eqww0+vwk8zAYWDjrqMtj7BJ63u9f4g/UxCjJGDyRmcSctxlx2oKmUHhBDCI/r3759vWavVUr16dbp27UqTJk18MyghhP84vhlWjITMZNCHQd+ZQd1vQJTN7K2zmbt9LgCL+y+mW4NuZdqPvYLKDghRmVy8eJGOHTvSrVs3Vq9eTfXq1fnrr7+oUqWKe52ZM2cyd+5cFi9eTIMGDXjhhRfo1asX+/fvx2hUSwEOGzaMM2fOsHbtWqxWKyNGjOCRRx5h2bJlHhmnN+akEnwNMtnO4GVEqH+9tD8c/YGJ6yby62m1OHFcWBwTb5nIqBtHEWYI46Uz+wHIMNk8dkyzNNwqkis7usjM1/Qz8Pm/4cRmAGyt76f/tlsxEUpEgDV184SazrqvR89nuc8vqfkqhBCeMXnyZF8PQQjhjxx22DQbNswAxQHVGqtlBuKb+Xpkws8s27eMcWvVTuSze85maIuhZd6XtYIabglRmbz66qvUrVuXRYsWuW9r0KCB+/8VReGNN97g+eefp1+/fgAsWbKE+Ph4kpKSGDp0KAcOHGDNmjXs2LHDnS371ltv0bdvX2bNmkWtWuWvn+yNOalEpYKMq+ZrmJ9kvm7/Zzvdl3Tntv/dxq+nfyXCEMELnV/g6JNHefrmpwkzhAEQZTQAkO7B4KtFgq9FCgtRn5fswjJfD/+gNjE4sRlCImHgB1zsPhsT6mX2xkpYSzchWj1ff//nEgBGg9Yvs8yFEEIIIYJCRgr8bwD8+LIaeG09DB75UQKv4grrj61neNJwAMa2H0tih8Ry7c+V+arzctkBIYJBRkYG6enp7n9ms7nA9b766ivatm3LPffcQ40aNbj++utZsGCB+/5jx46RnJxMjx493LfFxMTQrl07tm7dCsDWrVuJjY11B14BevTogVar5ZdffvHSIyw//0qPFOXmuoQ8wscBoT/O/sHzPz5P0sEkAEJ0ITze9nGe7fQsNSJqXLF+pFE9FTPNng++Ss3XgoUVlvlqt8GPL8Hm19Xl+JZqdkG1a8i5kA2oZS20lXAi4sp8/eN0OgBVI0LL3RhOCCEqO61WW+x7qUajwWbz3BxBCBEAnP0GyDoLhnC4fQ60rnxlr0Tx9qTsYcBnA7A6rAxuPphZPWeVe582Z81Xg06+SwpRnGbN8v8gNnnyZKZMmXLFekePHuXdd98lMTGRZ599lh07dvDkk08SEhLCgw8+SHJyMgDx8fH5touPj3ffl5ycTI0a+WNKer2euLg49zpl5c05qQRfg0yWjxtuHU87zpQNU/jf3v/hUBxoNVoebPUgk7tMpl5svUK3i3IGXzNMVo+NRRpuFc1V89Vic2B3KOqvupdOqbW0/t6mrtR2JPSaDgY16JhtdZ1flTPbM8EZfL2Uo56nUnJACCHKb+XKlYXet3XrVubOnYvD2XVaCFEJ2G1qv4GNrwEK1GgG9yyG6tf6emTCD52znOM/n/2HdHM6Xep1YXH/xWg15f/+Z3NUTMMtIYLB/v37qV27tns5NLTgptQOh4O2bdsyffp0QG1s9fvvvzN//nwefPDBChlrUbw5J5Xga5Bx1Xyt6OBYSmYKL296mfm/zsfqUANTA5sO5MVuL9KsevGXBUW7g68erPlqdZYd0FXOQGFx8p4jOVY7kSfWqd1jcy5CaDTc+Sa0GJhvmyz3+VU53zpcma8uVSMl+CqEEOXlqumV16FDh3jmmWf4+uuvGTZsGNOmTfPByIQQFS79DHw+Ek5sUZdveBD6vArOUmVC5JWak8rUI1M5bT5N8+rNSRqahFFvLH7DErA5pOarECUVFRVFdHR0sevVrFnziizZpk2b8vnnnwOQkJAAQEpKCjVr1nSvk5KSQuvWrd3rnD17Nt8+bDYbqamp7u3LyptzUkkJDDLuzNcKarh1yXSJF9a/QMO5DXlr+1tYHVZ6XN2D7f/ezueDPy9R4BUgMlSt+ZrpyZqvdqn5WpRQvRaNBvTY0H7/PCwbrAZea7aGR3+6IvAKuWUtKnvmq4tkvgohhGedPn2ahx9+mJYtW2Kz2di9ezeLFy+mXr3Cr54RQgSJv36A+R3VwGtIJAz6EO6aK4FXUSCTzcTdK+7mlPkUtaNqs3rYamKNsR7bv9XuynyV75JCeErHjh05dOhQvtv+/PNP9zyvQYMGJCQksG7dOvf96enp/PLLL3To0AGADh06kJaWxs6dO93rrF+/HofDQbt27Tw2Vk/PSStn+loQy66gmq851hze3v42r2x5hdScVABurHUjM7rPoPvV3Uu9P6+UHZCGW0XSaDQ0NFzgNd4kfOdh9cZ2j8Ft00Bf8GUCuWUtKmfwNcpoICpUT4azNnFVCb4KIYRHXLp0ienTp/PWW2/RunVr1q1bR6dOnXw9LCFERbi830BCS7j7I6h2jU+HJfyX3WHn/pX3s/nvzYRrw/lqyFfUjanr4WM4M1+l7IAQHjN27Fhuvvlmpk+fzuDBg9m+fTvvv/8+77//PqDGKMaMGcNLL71Eo0aNaNCgAS+88AK1atWif//+gJop27t3bx5++GHmz5+P1Wpl9OjRDB06lFq1apV7jN6ak0rwNchkW7x7WbjVbmXhroVM2ziN0xmnAWharSkv3/oy/Zv0L3PzoSgvlB2QhlvFOLCKL7TPEE0W9pAYdAPmQdM7i9wkx8vnVyBIiDGScTYTgKqRBQephRBClNzMmTN59dVXSUhI4JNPPinwki8hRJC6vN/Ajf+Gni+7+w0IcTlFUUj8LpEV+1cQogthYv2JtKzR0uPHcWe+StkBITzmxhtvZOXKlUycOJFp06bRoEED3njjDYYNG+ZeZ/z48WRlZfHII4+QlpbGLbfcwpo1azAacz8Xli5dyujRo+nevTtarZZBgwYxd+7cco/Pm3PSyhtBCVJZZu9kJjoUB//3x//xwo8vcDhVzZK8KuYqpnadyv3X3Y9OW77jRTqDr5kWGw6HgracvzA6HIqUHSiMzQxrJ8Mv7xIN7HY0xNDvI5o3va7YTSt75iuowde/nMFXKTsghBDl98wzzxAWFsY111zD4sWLWbx4cYHrffHFFxU8MiGEVx1aA0mP5fYbuGsuNB/g61EJPzd762zmbleDLAvvXEjk8UivHMfuarilk++SQnjSHXfcwR133FHo/RqNhmnTphVZWzUuLo5ly5Z5fGzenJNK8DXI5FidZQdCPRMcUxSF1YdX89z659idvBuA6uHVeb7z8zza5lFCC7k8vbSijQbn8dQAX5RzuaxcgVeQ4Gs+qcdg+XA4sxuA5SH9eTZ9IItDS5aeX9lrvkL+pltSdkAIIcrvgQceKPOVM0KIAGSzwLqpsPVtdbnW9XD3Iohr4NtxCb+3bN8yxq0dB8DsnrMZ3Gww3x7/1ivHstml7IAQlY0356QSfA0ynuxGv+XkFiaum8imk5sAiA6N5ukOTzOm/RiiQqPKvf+8QvVaDDoNVrtChsnDwVf5tVL1RxJ89QSY0yGsCvR/l4/XRmFNv+QO2hfHfX5VUEM3f5QQk9v0QcoOCCFE+X300Ue+HoIQoqJcPAErHoJ/flWX2z0Ot00ttN+AEC7rj61neNJwAMa2H0tih0SsVs/1C7mczSENt4SobLw5J628EZQgle2By8L3JO/hufXP8c1f3wBg1BsZfeNonrnlGaqGV/XIOC+n0WiIDNVzMdvqkbqvrnqvIDVfsZrg++dgxwfqct12cPdCiKmDccNWILdWcHGyrc7zyyCZryCZr0IIIYQQJXZgFXz5HzBdAmMM9HsHmhZ+6akQLnuS9zDgswFYHVYGNx/MrJ6zvH5Md/BVar4KITxAgq9BxOFQ3BmMZcl8PZJ6hEkbJvHJvk9QUNBpdDx0/UNM6jKJOtF1PD3cK0QZDVzMtpJpLv8vmK7ga4hOW7kvZbxwBJY/CMn71OVbxkK350CnZha7gvQlzXzNlsxXEvIEX6XmqxBCCCFEMWxmWDsJfpmvLtduC/csgtirfDsuERBOXjpJ32V9STen06VeF5b0X4JW4/3kGquUHRBCeFDljaAEIZPNjqL+QFeqmq+nM07z4k8v8sGuD7A51MzGIc2HMK3bNK6teq03hlqgKGfTrXQPZL6anMHESl3vdd8K+PopsGRCeFUY8D406pFvlTBX8LWkma9S85VazrIDYQZdpX4ehBBCCCGKlXoUlo9w9xvg5ieg+2R3IoAQRbmYc5E+S/twOuM0zas3J2loksd6jhTH3XBLgq9CCA+Q4GsQcdXjBDDqiw8KpeakMnPLTOb+MpccWw4Afa7pw8u3vsz1Na/32jgLE+nMpvRE2YG0HDV7NiasEk7srDmwejz8tkRdrtcRBn0A0Vc21QozqM95iTNfPVDWItBdGx/JAx3q0aBaROXOqhZCCCGEKMofK+GrJ3P7DQx4D67t5etRiQBhspno92k/9p/bT+2o2qwetppYY2yFHd9qd5UdqMTJPEIIj5HgaxDJ24leW8QvdFmWLN785U1mbpnJJfMlAG6uezMzus+gc73OFTLWgriabGV6IPiammkBoGpkJbss/NwhWD4czu4HNNB5HHSZALqC/9TDQtTJRIlrvlo819AtUGk0Gqb1a+HrYQghhBBC+CerCb57Fn79UF2u2x7u/hBivF/GTAQHu8PO/SvvZ9PJTcSExrB62GrqxtSt4DE4yw5IzVchhAdU3ghKEMpyZyUW/LJa7Bbe3/k+L218iZSsFACui7+O6bdOp2+jvj7P4os2ujJfy1/zNTVLDb5Wqpqcuz+BbxLBmg0RNWDg+9CwW5GbuM4Vk2S+CiGEEEKI8jp/WE0ESHH1G0h09huQr52iZBRFIfG7RFbsX0GILoSkoUm0jG9Z4eOw2aXsgBDCc+RTMIgUFhizO+ws27eMyRsmcyztGABXV7maF7u9yNAWQyukYHlJRBo9V3bgQmUKvlqy4NtxsHuputygMwz8AKLii93UaFDPFde5Uxyp+SqEEEIIIQq0dzmsGuPsN1ANBr4H1/QodjMh8pq9dTZzt88FYEn/JXSt39Un47C5a776x3dlIURgk+BrEHHVfHUFxhRF4atDX/Hc+uf449wfACREJjCp8yRG3jCSEJ1/BSZdDbcyzR4IvmaaAaga7MHXlP1qdsH5Q6DRQteJ0Om/oC1ZcDTc3XDLUaL1peyAEEIIIYTIx5INaybk6Tdwi7PfQE3fjksEnGX7ljFu7TgA5vScw5AWQ3w2FpuUHRBCeJBEUIKIKzAWEapnw/ENTFw3kW2ntgEQa4zlmY7P8ES7Jwg3hPtymIVy1XxN92DZgaqRFdMNs8IpCuz6H3w7Hmw5EJmgTnIbdCrVbsKcma851pJmvkrZASGEEEII4XR5v4Eu46HzeCkzIEpt/bH1DE8aDsDY9mMZ22GsT8fjbrglma9CCA+QT8Ug4gqMHbiwm26LRwEQbgjnqXZPMe7mcVQJq+LL4RUrSsoOlIw5A1Ylwr7/U5cb3goD3ofI6qXeVZg787W0Dbck+CqEEEIIUantXgbf/De338CgBXB1V1+PSgSgvSl7GfDZAKwOK4ObD2ZWz1m+HhJ2h9R8FUJ4jgRfg8TB8wd5c9vHQAfOZ/+DIczAI20e4fnOz5MQmeDr4ZVIZKiz7IAHgq/uzNdgC74m71OzCy4cBo0Obn0eOo6BMv4iG+au+Vp88FVRlHzZ1UIIIYQQohKyZME3T8OeZepygy4wcEGJ+g0IcbmTl07SZ2kf0s3pdKnXhSX9l/hFTxKrXcoOCCE8RyIoAe7kpZNM3TCVj/Z8RKSlH1XoQP24mnw68iBXV7na18MrlWhn2YEMc/nLDrhqvgZN5quiwK8LYc1EsJshujYM+hDqdSjXbl0ZrCZr8cFXi93h/gU4TDJfhRBCCCEqn5T9sPxBOP+ns9/As9ApscT9BoTIKzUnld4f9+Z0xmmaV29O0tAkQvX+UTbOnfmq830gWAgR+CT4GqDOZZ1jxuYZzNsxD4tdzfJsUrU1KSnQ85ouARd4Bc+VHVAUxV12oFow1Hw1pcPXT8IfK9XlRr1gwHwIjyv3rkuT+Zptzl0n3CATbCGEEEKISkNR1IZaq8eDzQRRNdV+A/Vv8fXIRIAy2Uz0/7Q/B84foHZUbVYPW02sMdbXw3Kz2aXsgBDCcyT4GmDSzenM2TqH2Vtnk2nJBKBLvS7M6D6D9XtjWJByLGA70UcaPVN2INtix2xTLxMJ+MzX07tg+Qi4eAy0eugxBdqPKnOZgcu5a76WIPM127lOiF4rvwALIYQQQlQW5gxYNRb2LVeXr+kBA96DiGq+HZcIWHaHnftX3s+mk5uICY1h9bDV1I2p6+th5WN1OMsOSPBVCOEBgRmlq4RMNhPv7niX6Zuncz77PAA31LyB6bdOp2fDnmg0Glb9ug8I3GZIUa6yA+UMvrrqvYbqtQH7XKAosP19+P55sFsg5iq4eyHUvdGjhylNw61ss/q6RATqcyqEEEIIIUrnzF5YMSK330D3F+DmpzyWCCAqH0VRSPwukRX7VxCiCyFpaBIt41v6elhXyC07IMFXIUT5SfDVz9kcNhbvXszUn6byd/rfAFxb9Vpe7PYidze7O18xcnczpADNfHWVHbDYHZisdoxlvLT9Qp5mWxpNAH5Y5lyEL0fDwVXqcpM7oN/bEFbF44cKN6jPeYkyX53nV6BmVgshhBBCiBJSFPj1Q1jzbG6/gbsXwlXtfT0yEeBmb53N3O1zAVjSfwld63f17YAKYXWXHZAfGoQQ5SdRFD+lKAqfH/ic59c/z6ELhwCoE12HyV0mM7z1cPTaK1+6LGdmYqA2Q8obNM4028oefHU124oMwJIDp3bCiuGQdhK0Buj5ErR7FLwURDaGqJOJHKsdRVGKDFZnWdTzK2CziYUQQgghRPFMl+Drp3L7DVzbG/q/65F+A6JyW7ZvGePWjgNgTs85DGkxxMcjKpxdyg4IITxIgq9+RlEU1h5dy7PrnmXnmZ0AVA2ryrOdnuU/N/4Ho95Y6LbuzNfQwAyO6bQaIkP1ZJptZJhsZW6WlZv5GkDNthQFts6DHyaDwwZV6sPdi6D2DV49rCuLVVHAZHUUGbjPcWe+Bub5JYQQQgghinF6FywfDhePO/sNTIUOo7yWCCAqj/XH1jM8aTgAY9uPZWyHsb4dUDHcDbek14UQwgMk+OpHtp3axsR1E9lwfAMAkSGRJLZP5L83/5fo0Ohit892ZyYG7ssaZXQFX61l3kdqnrIDASE7FZL+A3+uVpeb9YO73gJjjNcPHZYnuzjHai8y+JolZQeEED7icDhIS0sr8fqxsbFo5TJBIYQouYL6DdyzCOq09fXIRBDYm7KXAZ8NwOqwMrj5YGb1nOXrIRXLJjVfg5bMK4UvSBTFD/x+9neeW/8cXx36CoAQXQj/afsfnu30LNUjqpd4P4Fe8xUgMlQde2Y5mm65gq9xgRB8PfkLrHgI0k+BLhR6T4e2Iyssu0Cn1RCi12KxOci22Ip8znKk7IAQwkfS0tKYs2oXxoioYtc1ZWWQeMf1xMXJ5bF5bdy4kddee42dO3dy5swZVq5cSf/+/d33K4rC5MmTWbBgAWlpaXTs2JF3332XRo0auddJTU3liSee4Ouvv0ar1TJo0CDefPNNIiMj3evs3buXUaNGsWPHDqpXr84TTzzB+PHjK/KhCiFKqwL7DYjK5+Slk/RZ2od0czpd6nVhSf8l+fqW+CubXcoOBCuZVwpfCNwoXRA4dvEYkzdM5uO9H6OgoNVoGd5qOJO7TuaqmKtKvT9XTc5ArfkKuU230ssRfD0fCDVfHQ74+U1Y9yIodohrCPd8BDWvq/ChhBl0WGxqk7OiZJmdma+h8rYhhKh4xogoIqJjfT2MgJWVlUWrVq146KGHGDhw4BX3z5w5k7lz57J48WIaNGjACy+8QK9evdi/fz9Go1ryaNiwYZw5c4a1a9ditVoZMWIEjzzyCMuWLQMgPT2dnj170qNHD+bPn8++fft46KGHiI2N5ZFHHqnQxyuEKKFTv8KKEWq/AV2I2m/gpkekzIDwiNScVHp/3JvTGadpXr05SUOTCNUHRmk4q0MabgUzmVeKiiZRFB9IzkzmpY0v8f7O97E61MvrBzUdxIvdXqRp9aZl3m9OgNd8BYgyGgA8Unagmr/WfM06Dysfg8Nr1eUWd8Odb0Bo8b+8eUN4iI5LOVZ35nRhcpzB2fAyNkITQgjhO3369KFPnz4F3qcoCm+88QbPP/88/fr1A2DJkiXEx8eTlJTE0KFDOXDgAGvWrGHHjh20batehvzWW2/Rt29fZs2aRa1atVi6dCkWi4WFCxcSEhJC8+bN2b17N3PmzJHgqxD+RlFg69vww5TcfgP3fAS1rvfxwESwMNlM9P+0PwfOH6B2VG1WD1tNrDHW18MqMbuUHRBCeJD8jFOB0kxpPLfuORrObci8HfOwOqzcdvVt7Hh4BysGryhX4BVyMxMDuuyAM/M1I1jLDhzfAvNvUQOveiPcORcGfeCzwCvk1n3NKSb4mmUO/MxqIYQINhkZGaSnp7v/mc3mUu/j2LFjJCcn06NHD/dtMTExtGvXjq1btwKwdetWYmNj3YFXgB49eqDVavnll1/c63Tu3JmQkNzP3169enHo0CEuXrxY1ocohPC07FT4ZKha39Vhg2b94dGNEngVHmN32Ll/5f1sOrmJmNAYVg9bTd2Yur4eVqlYpeyAEMKDAjdKF0Cyrdm89ctbvLrlVS6a1C8fN9W+iRndZ3Brg1s9cgyHQ3FnJgZycCzaGXzNNJc9+Hoh0xl89aeyAw47bJoDG6aD4oBq16rZBfHNfT0y9/mSXUzZgewgyKwWQohg06xZs3zLkydPZsqUKaXaR3JyMgDx8fH5bo+Pj3ffl5ycTI0aNfLdr9friYuLy7dOgwYNrtiH674qVaR+pBA+d3IbrBiZp9/ADGj7kJQZEB6jKAqJ3yWyYv8KQnQhJA1NomV8S18Pq9Rcma8GneSrCSHKT4KvXmS1W/lw14dM+2kaZzLPANCsejNevvVl+jXuh8aDk5ycPIGzQM589UTZgQtZatZPVX/JfM08C188DEc3qMut7oW+syA0ssjNKoor89VUXNkB5/3hAXx+CSFEsNm/fz+1a9d2L4eG+mnJHSGEbzkcsOUNWP+Sz/sNiOA2e+ts5m6fC8CS/kvoWr+rbwdURja7GnzVSearEMIDJIriBQ7Fwae/f8qkHydx5OIRAOrF1GNat2kMazkMndbzmYOuZlsaDRgNgfvrXGRo+coOZFtsmKzqJSJVI/3gC+jRn+Dzf0PWWTCEq0HX64f5elT5uDNfiys74DzHwgM4s1oIIYJNVFQU0dHR5dpHQkICACkpKdSsWdN9e0pKCq1bt3avc/bs2Xzb2Ww2UlNT3dsnJCSQkpKSbx3XsmsdIYQPZJ2HlY/C4R/U5Zb3wB2v+7TslQhOy/YtY9zacQDM6TmHIS2G+HhEZWdzOMsOSM1XIYQHSPDVgxRF4du/vuW59c+xJ2UPADUiavB8p+d5pM0jXu3smG3ObYbkyYzaihblqvlaxrIDrpIDIXotEb4MEjrs8NOr8NNMQIHqTdXsghpNfDemQrhrvhZTdiA381WCr0KIsnE4HKSlpZV4/djYWLTSZdjrGjRoQEJCAuvWrXMHW9PT0/nll194/PHHAejQoQNpaWns3LmTNm3aALB+/XocDgft2rVzr/Pcc89htVoxGNQrWdauXUvjxo2l5IAQvnJ8C3w+EjLOqP0G+r4G198vZQaEx607uo7hScMBGNt+LGM7jPXtgMrB4VBwVh1AL/MQIYQHSPDVQzad2MTEdRPZ8vcWAKJDoxl/83ieav8UkSHev7zclbUYHhrYL2lu2YGyBV9dzbaqRoT4LgidfkYtM3B8k7p8/f3QZyaEhPtmPMVwBVOLbbjlznwN7HNMCOE7aWlpzFm1C2NE8dlWpqwMEu+4nri4uAoYWfDLzMzk8OHD7uVjx46xe/du4uLiuOqqqxgzZgwvvfQSjRo1okGDBrzwwgvUqlWL/v37A9C0aVN69+7Nww8/zPz587FarYwePZqhQ4dSq1YtAP71r38xdepURo4cyYQJE/j999958803ef31133xkIWo3ArsN7AY4psVv60QpbQneQ8D/28gVoeVwc0HM6vnLF8PqVyszqxXkMxXIYRnSBSlnHYn7+a59c/x7V/fAmDUG3nypieZcMsE4sIq7gtjtjMw5tNsTw/ILTtQtpqvrnqvcb6q93p4HXzxCGSfB0ME3PkGXDfYN2MpIVfZAcl8FUJUBGNEFBHRsb4eRqXz66+/0q1bN/dyYmIiAA8++CAfffQR48ePJysri0ceeYS0tDRuueUW1qxZg9FodG+zdOlSRo8eTffu3dFqtQwaNIi5c+e674+JieH7779n1KhRtGnThmrVqjFp0iQeeeSRinugQgi138Dn/4ZjP6nLrf4Ft8+CkAjfjksEpRNpJ+iztA/p5nS61OvCkv5L0GoCO1vU1WwLQC81X4UQHiDB1zL668JfTNowiU9//xQAnUbHv2/4Ny90foHa0bWL2drzsoKkGVK0s+xAZhkzX11lByq83qvdBj++DJvnqMvxLdUyA9WuqdhxlEGYQX3Oi6/5GhznmBBCVEZdu3ZFUZRC79doNEybNo1p06YVuk5cXBzLli0r8jjXXXcdmzZtKvM4hRDldHQDfP5wbr+B22dD63/5elQiSKXmpNJnaR/OZJ6hefXmJA1N8mqpvYpitecNvgZ2IFkI4R8kilJK/6T/w7SfpvHhrg+xK2ow6t4W9zKt2zSuifNdoC3bHBzNkDxZdqDCXPpHraV1cqu63PYh6DUdDGEVN4ZyCAtRJxQmyXwVQgghhAhMl/cbqNFMTQSo3tjXIxNBymQz0e/Tfhw4f4DaUbVZPWw1scZYXw/LIyTzVQjhaRJ8LaEL2Rd4dcurvLX9LUw2EwC3N7qdl299mVYJrXw8umCq+Vq+sgOu4GuFlR3483u1e2xOKoREwV1zocXAijm2h7gyWV2lKwrjqvkaESrBVyGEEEIIv3F5v4EbHoDer/ptvwER+OwOO/d9cR+bT24mJjSG1cNWUzemrq+H5TE2u1rzVasBrQRfhRAeENiRugqQacnkjW1v8NrPr5FuTgfglqtuYUb3Gdxy1S0+Hl2uoKn56gy+Zlns2B0KulJ+2F2oqOCr3QrrpsHPzlp3NVup2QVxV3v3uF5gNLhqvjqKXM8V4A+TsgNCCCGEEP7h8A/wxaNqv4GQSLjjDbjuHl+PSgQxRVEY+91YPj/wOSG6EJKGJtEyvqWvh+VRNmfmq14nJQeEEJ4hUZRCmG1m3t/5Pi9teomzWWcBaBXfiundp9Pnmj5oNP71C1iWOzAW2MFXV+YrQKbZRkyYoVTbX8hUG25Vi/Ri8DXtJKx4CE7tUJdvehR6vggBWt/IVUYgp4jMV5vdgcWmBmcDPcAvhBBCCBHw7Db48SXY/Lq6HED9BkRgm/XzLN7a/hYAS/ovoWv9rr4dkBfYnDVfpeSAEMJTJPh6GbvDzsd7P2byhsmcuHQCgIZVGvJitxcZ0mKI33ZudGUlRgR4VmKoXkeIXovF5iDDZC118DW37ICXAqEHv4Gkx8F0CUJjoN/b0Owu7xyrgoS5M18Lr/manee+QA/wCyGEEEIEtEunYMVI+Hubutx2pLPfgNG34xJBb9m+ZYz/YTwAc3rOYUiLIT4ekXdYHWrSiQRfhRCeEtiROg9SFIUvD33Jc+ufY/+5/QDUiqrFpM6TeOj6hzDoShcErGjuhltBUI8zKlTPBZuFTHPpm255reyAzQJrJ8Ev76rLtdvA3QuhSn3PHscHXMFUVwC/INlm9T69VkOIXH4jhBBCCOEbf37n7DdwEUKj4c43A67fgAhM646uY3jScADGth/L2A5jfTsgL7JL2QEhhIdJ8NVJQWHyhsnsP7efKsYqTLxlIqNvGk1YgHSsd5UdCDcE/ksaZdRzIctChqn0wVdX5mtVTwZfU4/BihFwepe63GE0dJ8M+gpq6uVluWUHigi+OksShIXo/K7khhBCCCFE0LNbYd1U+Fm93JuareGeRQHZb0AEnj3Jexjw2QCsDiuDmw9mVs9Zvh6SV1ntkvkqhPCswI/UeYhWo+XVHq+y+eRmnr75aWKNsb4eUqnkBFEn+iijmmWcYbKWarsci92dvVnVUzVf/0iCr54AczoYY2HAfGjcxzP79hMlKjsQJGUthBBCCCECTtpJWD4C/vlVXW73GNw2LWD7DYjAciLtBH2W9iHDkkGXel1Y0n+J35bi8xRX5qtBMl+FEB4i7yZ59L6mNy/d+lLABV4hT+ZrEATHIkPVx1DazNcLWWqzrRCd1r2PMrOa4Jv/wvIH1cBr3Xbw2OagC7xCbtmBojNfXedX4Af3hRBCCCECxoFVMP8WNfBqjIEhH0OfVyXwKipEak4qfZb24UzmGZpXb07S0CRCK8G5Z3U23NJJ5qsQXvXKK6+g0WgYM2aM+zaTycSoUaOoWrUqkZGRDBo0iJSUlHzbnTx5kttvv53w8HBq1KjBuHHjsNlKf+V0RQr8SJ0Aci8LD4bgWJSxbMHX1Dz1Xst1afyFI7B8OCTvVZc7joFbnwc/r/tbVu7M1xKWHRBCCCGEEF5WYL+BRVClnm/HJSoNk81Ev0/7ceD8AWpH1Wb1sNUBmaRUFrk1XyX4KoS37Nixg/fee4/rrrsu3+1jx47lm2++Yfny5cTExDB69GgGDhzIli1bALDb7dx+++0kJCTw888/c+bMGR544AEMBgPTp0/3xUMpEcl8DRLBlJmYW3agtJmvHmi2tW8FvNdZDbyGV4VhK+C2qUEbeIXcbGkpOyCEEEII4QdSj8HCnrmB1w6jYcQaCbyKCmN32Lnvi/vYfHIzMaExrB62mroxdX09rApjk5qvQnhVZmYmw4YNY8GCBVSpUsV9+6VLl/jwww+ZM2cOt956K23atGHRokX8/PPPbNu2DYDvv/+e/fv38/HHH9O6dWv69OnDiy++yLx587BYLL56SMWS4GuQcHWjjyjv5fZ+wJX5mmkuXc3XC5nOZltlqfdqzYGvn4LPR4IlE666WS0z0Oi20u8rwLgyX20OBYvNUeA6ruCrZL4KIYQQQnjRH0lqIsDpXRBWBe79DHq9HDSNXoX/UxSFsd+N5fMDnxOiCyFpaBIt41v6elgVyurKfNVKuESIksjIyCA9Pd39z2w2F7n+qFGjuP322+nRo0e+23fu3InVas13e5MmTbjqqqvYunUrAFu3bqVly5bEx8e71+nVqxfp6en88ccfHnxUnhX4kToBQJaUHSDVWfO1amkzX8/9qZYZOPsHoIHOT0OXZ0BXOf488gZUc6x2QvRXTjKyg6ihmxBCCCGE37Ga4PvnYMcH6nLd9nD3hxBTx7fjEpXOrJ9n8db2twBY0n8JXet39e2AfMDucGa+StkBIUqkWbNm+ZYnT57MlClTClz3008/5bfffmPHjh1X3JecnExISAixsbH5bo+Pjyc5Odm9Tt7Aq+t+133+qnJElyqB7CBquFXW4Gtu2YFSFIHf/Ql8kwjWbIioDgMXQMNupTpuoDPoNOi0GuwOhRyLnZiwK0ssuDNfDYF/fgkhhBBC+JULR9Qmr8n71OVbxkK354K67JXwT8v2LWP8D+MBmN1zNkNaDPHxiHzD1XBLyg4IUTL79++ndu3a7uXQ0IJjMn///TdPPfUUa9euxWg0VtTw/IJEUoJEMDXcigwtW83X1NKUHbBkwbfjYPdSdblBZzXwGpVQqmMGA41GQ7hBR4bZVmjd12yzZL4KIYQQQnjcvhVq6StLptpvYMD70KhH8dsJ4WHrjq5jeNJwAMa2H0tih0TfDsiHchtuSdkBIUoiKiqK6OjoYtfbuXMnZ8+e5YYbbnDfZrfb2bhxI2+//TbfffcdFouFtLS0fNmvKSkpJCSosZqEhAS2b9+eb78pKSnu+/yVvJsEAbtDwWRVL40IppqvGabS1XxNLWnDrbMHYMGtauBVo4Wuz8L9SZUy8OpidAbtXUH8y0nNVyGEEEIID7LmwFdP5vYbqNfR2W9AAq+i4u1J3sOAzwZgdVgZ3Hwws3rO8vWQfMoqDbeE8Iru3buzb98+du/e7f7Xtm1bhg0b5v5/g8HAunXr3NscOnSIkydP0qFDBwA6dOjAvn37OHv2rHudtWvXEh0dfUX5A38S+JE6kS9gFgyZr2UtO3DeGXwttOarosCuj9WMV1sORCbAoA+gQadyjTcYuM4bUyGZr1nO4GtEEJS1EEIIIYTwqXN/qmUGzu5H7TcwDrpMqDT9BoR/OZF2gj5L+5BhyaBLvS4s6b8EraZy52hJ5qsQ3hEVFUWLFi3y3RYREUHVqlXdt48cOZLExETi4uKIjo7miSeeoEOHDrRv3x6Anj170qxZM+6//35mzpxJcnIyzz//PKNGjSq03IE/kE/4IJDjDIxpNRBaQLOkQOMOvppLm/nqbLhVUNkBcyasGgv7/k9dbnirellXZPVyjTVYhBlcma8FB19zgqishRBCCCGEz+TrN1ADBr5f6foNCP+RmpNKn6V9OJN5hubVm5M0NIlQvf8GLyqKTWq+CuEzr7/+OlqtlkGDBmE2m+nVqxfvvPOO+36dTseqVat4/PHH6dChAxERETz44INMmzbNh6MungRfg0DerESNJvA/IKKMas3XzDLWfL2i4VbyPlg+HC4cBo0Obn0OOo4FbeAHqj3FVU4gp5Dga1YQNXQTQgghhKhwBfYb+ACi4oveTggvMdlM9Pu0HwfOH6B2VG1WD1tNrDHW18PyC1aHlB0QoqJs2LAh37LRaGTevHnMmzev0G3q1avHt99+6+WReZZEUoJAlrMZUrDU48xbdkBRlBIFlE1WuztA6K75qiiwcxGsfgbsZoiqBXcvhHodvDb2QOXKfC2s4VaOO/gaHOeYEEIIIUSFOXtATQQ4d9DZb2AidPovaGVeJXzD7rBz3xf3sfnkZmJCY1g9bDV1Y+r6elh+I7fsgARfhRCeIcHXIOAKmAVDsy2ASOfjsDkbiZUkqHzBWe/VoNMQbdSDKV3tHPvHF+oKjXpC//kQUdVr4w5k4cVmvkrZASGEEEKIUlEU2PU/+Ha89BsQfkNRFMZ+N5bPD3xOiC6EpKFJtIxv6eth+RWru+yAXCkphPCM4IjWVXKuzNdgCYyp5RPU+WqG2Vqi4GtuyYEQNGf2qNkFF4+BVg/dJ0OH0VJmoAjGYmu+StkBIYQQQogSM2fAqsQ8/Qa6w4D3pN+A8LlZP8/ire1vAbCk/xK61u/q2wH5Ibur7IBkvgohPEQiKUEgO8g60Wu1GiJD9WSYbGSYbNSIKn6bC1lmQOFB3ffw4SKwWyCmrlpmoO5NXh9zoHNnvhZSdsCd+RoaHAF+IYTwJw6Hg7S0tFJvI4TwU1f0G3geOo6RRADhc8v2LWP8D+MBmN1zNkNaDPHxiPyTVRpuCSE8LDiidZWcK/gaLDVfAaLyBF9LIiPtPO8a3qBPzg71hsa3Q7+3ITzOi6MMHu6ar8VmvgbPOSaEEP4iLS2NOat2YYwowa+NgCkrg0Et5fNNCL+jKPDrQlgzUe03EF0bBn0o/QaEX1h3dB3Dk4YDMLb9WBI7JPp2QH4st+ar/GAihPAMCb4GgWxnVmJEEGUlRhkNcMlEZkmCr6d20vXH+4jSncaGHn3vl6DdY1CCRl1CFebMmi6s7ECWObiyq4UQwt8YI6KIiI719TCEEGVlSoevn4Q/VqrLjXrBgPmSCCD8wp7kPQz4bABWh5XBzQczq+csXw/Jr9nszrIDkvkqhPAQv/gpZ968edSvXx+j0Ui7du3Yvn17oesuWLCATp06UaVKFapUqUKPHj2KXL8ycAXGgqkeZ5RRfSwZJmvhKykKbJ0HC3sRZTrNSUd1FjWZD+0fl8BrKbkzXwsoO+BwKO7bgym7WgghhMhL5qOizE7vgvc6q4FXrR56vgT3fiqBV+EXTqSdoM/SPmRYMuhSrwtL+i9Bq/GLMIDfsjqk4ZYQwrN8/m7y2WefkZiYyOTJk/ntt99o1aoVvXr14uzZswWuv2HDBu69915+/PFHtm7dSt26denZsyf//PNPBY/cf2QHYSf63OBrwZmvBlsmuuX3wXfPgsPK3ugu3GGZjrlG6wocZfBw13y1XPl8m2y5AVnJfBVCCBGMZD4qykRR0O5YAB/2VBu9xlwFI9bAzU9IfVfhF1JzUumztA9nMs/QvHpzkoYmEaoP9fWw/J6r7IBBGm4JITzE57OCOXPm8PDDDzNixAiaNWvG/PnzCQ8PZ+HChQWuv3TpUv7zn//QunVrmjRpwgcffIDD4WDdunUVPHL/kR2EnegjjQYAMsxXBgM1p7bT9eDzaP/6DnQh0HcWc+OeJ50I4iJkMlEWxiIabrkyqzUaMBp8/pYhhBBCeJzMR0WpmS5x47G30H0/UW302uQOeGwj1L3R1yMTAgCTzUS/T/tx4PwB6kTXYc19a4g1xvp6WAHB6iw7oJOyA0IID/FptM5isbBz504mTpzovk2r1dKjRw+2bt1aon1kZ2djtVqJiyv4sh6z2YzZbHYvZ2RkAGC1WrFai7ikPYBkmiwAGPWaoHlMESFqkO9Sljn3MSkOtNveRvfjy4QrdhyxDbAP+hASruPc9l8AiDXqguY5qEihzphqltl2xfOXnm0C1NIENlvJGqAVx3UMea0Ck7x+gc9Xr6HVakVR7DgcBdeXzktR7O7Patnuym1tNvlC6CkVMR+FyjEnrSw0//yGbuVIal36G0VrwNFjKo62D6u/VMtrGTCCeT5jd9j518p/sfnkZmJCY/hq8FfEh8UH3WP11mtodV75p0UJuufM3/ji77Ai52uux1WR25VnTlpa8vdRcj4Nvp4/fx673U58fHy+2+Pj4zl48GCJ9jFhwgRq1apFjx49Crx/xowZTJ069YrbN27cyP79+0s/aD/01zEtoOX44UN8m12y583fnftHfUx7D/7Ft6ZDhFjTueHk+8Sn7wXgVGx79lw1Attvp4BTnDqnAzQc2vsr1uM+HHiAOnBBA+g4nXKeb7/9Nt99/2QB6NEptivuK6+1a9d6dH+iYsnrF/gq+jXMyMjgyD9ajBFRxa5ryspgrekIUVFRsl0B2249fb5E64riVcR8FCrHnDToKQoNz62h2T//hxY7WSE1+LXBf0g7VwdWr/b16EQZBdt8RlEUPvjnA745/w16jZ6n6zzNyV9PcpKTvh6a13j6NTzq/H599MhffGv+06P7FgWryL/DipyvrTUdAajQ7cozJy2t8+dlPlpSAX2d+iuvvMKnn37Khg0bMBqNBa4zceJEEhMT3cv//PMPzZo1o3PnztSvX7+CRupdX13cBRfO0bZ1S/q2rePr4XjE8Q1HWXf6MNVr1eX2FunoVo5Hk5mMojdi6f4iO1NqcFvPnhgManmCZ39bB9i5vUcXGlSL8O3gA1DEn+dY9OcujJHR9O3bId99u06mwd7txEaG07dvJ48cz2q1snbtWm677Tb3aygCh7x+gc9Xr2FqairHNh0lPCq22HWzM9K4rdPVxMXFyXYFbNuhXqMSrSu8ryTzUagcc9KglnMR3dej0f7zHQC2xnewIfQOuvXuJ5+FASpY5zOzt83mmz3fAPBRv48Y3Gywj0fkPd56DTet/APO/kOzJk3o27mBx/YrrlSe19DhcJCWllbi9WNjY9FqtRU6X7ut09UAFbpdeeakpXX8+PFSb1NZ+TT4Wq1aNXQ6HSkpKfluT0lJISEhochtZ82axSuvvMIPP/zAddddV+h6oaGhhIbm1gFNT08HwGAwBM2HbI5VrUkTFRYSNI8pNiIUDQ46JS9G//FHoDigaiM093yEtmpj+PZb92tottnddUnjYyKC5jmoSJFh6t+Iyea44vkzq6cXEaF6jz+3wfR3WBnJ6xf4Kvo1NBgMaDQ6tNriG0RqNDr3+GS7K7fV6wP693O/UhHzUagcc9KgdfIXWPEQpJ8CXSj0no7S6gFsq1fL6xcEguk1XLZvGRPXqyVU5vScw7BWw3w8oorh6dfQ2W+LEIMuaM4Nf1eW1zA1NZW3vvu9xNmdiXdcT1xcXIXO11yPqSK3K8+ctLTk76PkfNo9JyQkhDZt2uRrTuBqVtChQ4dCt5s5cyYvvvgia9asoW3bthUxVL+WFYQNt6qRxmLDq9x1YaEaeL1uKDyyARJaXLFuapZa81av1RAdFjzPQUUKdzXcslxZEya3oVvJ3vSFEEKIQCLzUVEohwM2vwGL+qiB17iG8O8f4MZ/q/VdhfAj646uY3jScAAS2ycytsNY3w4ogFmd0Ve9VpoN+ztjRBQR0bHF/ivppftCeIvPI1WJiYk8+OCDtG3blptuuok33niDrKwsRowYAcADDzxA7dq1mTFjBgCvvvoqkyZNYtmyZdSvX5/k5GQAIiMjiYyM9Nnj8KUci9oEKSJYgmNHf6LHxpGE6s5hJpTQfq/D9YX/anshUw2+xkWEoJGJcJmEGZzBV2tBwVfn+RXq87cLIYQQwitkPiqukHUeVj4Gh511CFvcDXe+AaHyBV74nz3Jexjw2QCsDitDmg/htZ6v+XpIAc3uUC/9M+jku6UQwjN8Hk0ZMmQI586dY9KkSSQnJ9O6dWvWrFnjbnpw8uRJtHl+cXr33XexWCzcfffd+fYzefJkpkyZUpFD9xuuS+7DAz045rDDTzPhp1cJReGQow6vRk5gYRGBV4ALWbnBV1E2Yc7AfXYRma+uAK0QQggRbGQ+KvI5vgU+HwkZZ0BvhD4z4YYHJNtV+KUTaSfos7QPGZYMutbvyuL+i9FqJGOzPKx2NfNVJ5mvQggP8Yto3ejRoxk9enSB923YsCHfshT0vVJ2MGS+ZiTD5/+G45sAuHjtEPrt7U20NbrYTVOzzABUjZTga1m5AqsWmwO7Q0Gnzf1yke0M7kvmqxBCiGAm81GBww6b5sCG6WrZq2rXwj0fQXxzX49MiAKl5qTSZ2kfzmSeoUWNFqwcspJQfWjxG4oi2V1lByTzVQjhIRJNCQKumq9hgRp8PbwOvngEss+DIQLueJ30Ondg2rsBrdlW7Oa5ZQdkolFWeesF51jtROYJtGYH+vklhBBCCFGczLPwxcNwdIO63Ope6DsLQqWMhPBPJpuJfp/248D5A9SJrsPqYauJNcb6elhBwWpXyw7otRJ8FUJ4hgRfA5zN7sBiUz8cIgKt4ZbdpmYWbJoDKBDfQs0uqNaIKGcpgWyLHZvdgV5X+CUfrrIDVaXsQJmF6nOf3xzL5cHXIMisFkIIIYQozNGf1MBrZgoYwtWgazFlr4TwJbvDzn1f3Mfmk5uJCY1h9bDV1Imu4+thBY3czFcpOyCE8IwAi9aJy2XnaZAUHhpAwbFL/6hlBk7+rC63GQG9Z4AhDCBf8C/TbCM2vPDAamqmBF/LS6vVEGbQkWO1k3NZ3dfczFd5uxBCCCFEEHHY4adX1Z4DKFC9qZoIUKOJr0cmRKEURWHsd2P5/MDnhOhC+HLol7So0cLXwwoqNmfNV8l8FUJ4ikRTApyrHqdOqyEkUH6Z+/N7WPko5KRCSBTc9Sa0GJRvlRC9llC9FrPNQYap6OCru+GW1Hwtl7AQZ/DVmj/4miWZr0IIIYQINuln1GxXZ78Brr9fbawVEu7bcQlRjFk/z+Kt7W8B8L8B/6NL/S4+HlHwsTqk7IConBwOB2lpaaVaX5SMBF8DnOuS8PAQHRp/78Bqt8K6afDzXHW5Ziu4exFUbVjg6lFGA+ZMMxmmouu+uhtuSeZrubiabrnOKRdXJmy4BF+FEEIIEQwu7zdw5xtw3WBfj0qIYi3du5TxP4wHYE7POQxuLuetN7jKDhgCJblJCA9JS0tjzqpdGCOiil3XlJXBoJZxFTCq4CDB1wDnuiTc7+u9pv0NKx6CU9vV5ZsegZ4vQRHdOKONes5nmskwWYvctbvma6Q03CoPV0OtyzNfs93BVz8/x4QQQgghinJFv4GWzn4D1/h6ZEIUa93RdYz4cgQAie0TGdthrI9HFLyszrIDOsl8FZWQMSKKiOhYXw8j6Eg0JcBlmXMzX/3WwW8h6XEwpUFoDPR7C5r1K3azSKN6ehab+eqs+Ronma/l4jqHrqz5GgDnmBBCCCFEUS79A5+PhJNb1eW2D0GvGWAw+nZcQpTAnuQ9DPhsAFaHlSHNh/Baz9d8PaSgZneVHdBJ8FUI4RkSfA1wroZbftlsy2aBHybDtnfU5Vo3wD2LoEr9Em0e5Qy+ZpoLD76abXYynPdL2YHyMRqKyXwNlbcLIYQQQgSgK/oNzIUWA309KiFK5ETaCfos7UOGJYOu9buyuP9itBq5HN6bchtuyfMshPAMiaYEOFfDLb+7JPzicVg+Ak7/pi63HwU9poC+5AHSqFADQJFlBy5mqffptBqijYayjlaQm9mafUXmq9R8FUIIIUQAKqjfwD0fQdzVPh2WECWVmpNK76W9OZN5hhY1WrByyEpCiyjbJjzDKpmvQggP87OInSgtv+xEv/9L+PIJMF8CYyz0fxea9C31blxlB9KLKDtwPlNtthUXEYJWavKUi6vhlumKzFdbvvuFEEIIIfxe2klnv4Ed6vJNj0LPF4vsNyCEP8mx5nDXJ3dx8PxB6kTXYfWw1cQaY309rErB7s58le+XQgjPkOBrgMvxp2ZIVhN8/zzsWKAu17kJ7l4IsXXLtLuSlB1IdTXbkpID5RZWWOarM7s6QsoOCCGEECIQHPwGkv6Tp9/A29DsLl+PSogSszvs3LfyPrb8vYWY0BhWD1tNneg6vh5WpWF1SNkBIYRnSTQlwGX5SzOkC0dg+XBI3qsud3wKbn0BdGUvBRBlLL7sgCv4Ks22ys+V2Zq34ZaiKLl1hX19jgkhhBBCFMVmgbWT4Jd31eXabdREgBL2GxDCHyiKwpg1Y/jiwBeE6EL4cuiXtKjRwtfDqlTszuCrQcoOCCE8RIKvAc4vshL3rYCvx4AlA8LiYMB7cG3Pcu82yvmYMoooO3BBgq8e4wqu5m24ZbY53JMPCb4KIYQQwm+lHoMVI+D0LnW5w2joPrlU/QaE8Aev/fwab+94G4D/DfgfXep38fGIKh+rXa35qpOyA0IID5E8+gDnynwN80VgzJoDXz8Fn49UA69X3QyPbfZI4BXylB0oIviamqXWfK0WKfW7yqugzNe8/+8XpS2EEEKUyZQpU9BoNPn+NWnSxH2/yWRi1KhRVK1alcjISAYNGkRKSkq+fZw8eZLbb7+d8PBwatSowbhx47DZCv+MFqLC7P8S3uusBl6NsXDvp9DrZQm8ioDz8d6PmfDDBADm9JzD4OaDfTyiyik381XCJUIIz5BoSoBzBccqvOHW+b/UMgMpvwMa6PRf6DoRdJ47pXLLDhSR+Zopma+eEuYMruat+eoK7ofqtfLLrxBCBLjmzZvzww8/uJf1+tzP7LFjx/LNN9+wfPlyYmJiGD16NAMHDmTLli0A2O12br/9dhISEvj55585c+YMDzzwAAaDgenTp1f4YxECuLLfQN12MOjDMvcbEMKXfjj6AyO+HAFAYvtExnYY6+MRVV42Z8Mt+f4jhPAUCb4GuCxfNNza8xmsGgvWLIioDgPfh4a3evwwrszX9CJqvkrZAc8JM6i/7JqsV2a+SskBIYQIfHq9noSEhCtuv3TpEh9++CHLli3j1lvVz/NFixbRtGlTtm3bRvv27fn+++/Zv38/P/zwA/Hx8bRu3ZoXX3yRCRMmMGXKFEJC5HNYVLAr+g2MgVufL1e/ASF8ZXfybgZ+NhCbw8aQ5kN4redrvh5SpWZ1qGUH9FLzVQjhIZJHH+CyzRXYcMuSBUmjYOUjauC1fie1zIAXAq8Aka6yA+aiyg6owdeqEnwtt3B35mvu8+2T4L4QQogSy8jIID093f3PbDYXuu5ff/1FrVq1uPrqqxk2bBgnT54EYOfOnVitVnr06OFet0mTJlx11VVs3boVgK1bt9KyZUvi4+Pd6/Tq1Yv09HT++OMPLz06IQqxbwW810UNvIZXhWGfw21TJfAqAtKJtBP0WdqHDEsGXet3ZXH/xWg18jXdVxwOBUVNfMWglddBCOEZ8m4S4FyXiId7u+HW2QOw4FbY/TGgUUsMPPAlRF2ZQeMp0cbiG26lSuarxxgLaLjlCsRK5qsQQvinZs2aERMT4/43Y8aMAtdr164dH330EWvWrOHdd9/l2LFjdOrUiYyMDJKTkwkJCSE2NjbfNvHx8SQnJwOQnJycL/Dqut91nxAV4vJ+A/U6qokAjXoUv60Qfig1J5XeS3uTnJlM8+rNWTlkJaF66WXhS66sVwCdZL4KITxE0tkCnCs45rWar4oCu5fCN0+DLQci42HQB9Cgs3eOl4er5mum2YaiKGg0V374nc9UM3yqSsOtcgsvoOFWtrmCgvtCCCHKZP/+/dSuXdu9HBpa8Odhnz593P9/3XXX0a5dO+rVq8f//d//ERYW5vVxClFu5/5Uywyc/QPQQOenocszHu03IERFyrHmcNcnd3Hw/EHqRNdhzX1riDXG+npYlZ6r2RZI5qsQwnNkthLgvHpZuDkTvkmEvZ+py1d3g4ELILK6549VgEhnwM/uUMix2q94jBabw50VK2UHyi+soMxX5/+7ArNCCCH8S1RUFNHR0aXeLjY2lmuvvZbDhw9z2223YbFYSEtLy5f9mpKS4q4Rm5CQwPbt2/PtIyUlxX2fEF6151NYlZin38ACaNjN16MSoszsDjv3rbyPLX9vISY0htXDVlMnuo6vhyUAqz03+CoNt4QQniI/5QQ4rzVESv4d3u+qBl41Wrj1BbjviwoLvIL6mFwfeAWVHriYrZYc0Gk1xIRJja/ycgVfsy15G245M6tDJfgqhBDBJDMzkyNHjlCzZk3atGmDwWBg3bp17vsPHTrEyZMn6dChAwAdOnRg3759nD171r3O2rVriY6OplmzZhU+flFJuPsNPKoGXht0dvYbkMCrCFyKovDUmqf44sAXhOhCSBqaRIsaLXw9LOGUN/NVL8FXIYSHSOZrgMvydHBMUWDnR7B6AtjNEFUL7v4Q6t3smf2XgkajITJUz6UcKxkmK/HRxnz3p2ZZAagSbkArH4zlFubMbjXlyXzNcpYdCJOGW0IIEdCefvpp7rzzTurVq8fp06eZPHkyOp2Oe++9l5iYGEaOHEliYiJxcXFER0fzxBNP0KFDB9q3bw9Az549adasGffffz8zZ84kOTmZ559/nlGjRhVa6kCIcjl7QC0zcO6gmgjQ5Rm11IBWfhAWgW3mlpnM2zEPgP8N+B9d63f17YBEPja7WvNVq0G+YwohPEYyXwOcuyanJ4JjpnS1gcGqMWrg9Zrb1OwCHwReXVylBwrKfL3gbLZVNUK+9HlCeEGZr85ArNdqCgshhKgQp06d4t5776Vx48YMHjyYqlWrsm3bNqpXV69oef3117njjjsYNGgQnTt3JiEhgS+++MK9vU6nY9WqVeh0Ojp06MB9993HAw88wLRp03z1kESwUhT47X/wfjc18BqZAA98BV0nSOBVBLyP937MM+ueAWBOzzkMbj7YxyMSl7M6M1/1OgmVCOFpM2bM4MYbbyQqKooaNWrQv39/Dh06lG8dk8nEqFGjqFq1KpGRkQwaNMhd6srl5MmT3H777YSHh1OjRg3GjRuHzVZ4o3Z/IOlsAcxqd2Bx/jJX7rIDZ/ao2QWpR0Gjgx6TocMT4OMi41HGwoOvqc7ga5zUe/UIV+ZrjtXubnCWZVaf9zAJvgohRED79NNPi7zfaDQyb9485s2bV+g69erV49tvv/X00ITIdXm/gYa3woD3K7TslRDe8sPRHxjx5QgAEtsnMrbDWB+PSBTE7qz5apCsVyE87qeffmLUqFHceOON2Gw2nn32WXr27Mn+/fuJiIgAYOzYsXzzzTcsX76cmJgYRo8ezcCBA9myZQsAdrud22+/nYSEBH7++WfOnDnDAw88gMFgYPr06b58eEWS4GsAy5uhWObMV0WBHR/Ad8+C3QIxdeHuhVD3Jg+NsnyijWot1wKDr86ar3GREnz1BFeAVVHAbHNgNOjc51iElB0QQgghhDcl/w7LH4QLh9VEgFufg45jfZ4IIIQn7E7ezcDPBmJz2BjSfAiv9XzN10MShbA61OQmabYlhOetWbMm3/JHH31EjRo12LlzJ507d+bSpUt8+OGHLFu2jFtvvRWARYsW0bRpU7Zt20b79u35/vvv2b9/Pz/88APx8fG0bt2aF198kQkTJjBlyhRCQvwzPiSzmQCW7az3atBpCNGX4aXMSYP/ewC+fVoNvDbuC49u9JvAK0CkM/M102y94r5Ud9kB//zjCjSuzFfIDey7zjHJfBVCCCGEVygK/LoQFtyqBl6jasHwb6DTfyXwKoLCibQT9FnahwxLBl3rd2Vx/8VoNXJu+ytXwy2DlB0QosQyMjJIT093/zObzSXa7tKlSwDExcUBsHPnTqxWKz169HCv06RJE6666iq2bt0KwNatW2nZsiXx8fHudXr16kV6ejp//PGHpx6Sx0k6WwBzN0MylCEw9s9OWD4C0k6A1gC3TYP2j4PGv37hK0nZAan56hl6nZYQnRaL3eGu9Zqb+SrBVyGCkcPhIDU1tcTrx8bGopVgiBDCU0zp8PVT8IezvnCjXtD/XYio6ttxCeEhqTmp9F7am+TMZFrUaMHKISsJ1ct3F39mtUvmqxCl1axZs3zLkydPZsqUKUVu43A4GDNmDB07dqRFixYAJCcnExISQmxsbL514+PjSU5Odq+TN/Dqut91n7+S4GsAy3EFxkJL8TIqCmx7F9ZOAocVYuvBPYugdhsvjbJ8XMHX9AKDr2o2rJQd8JywEB2WHAc5zoxXV/DVIw3dhBB+Jy0tjbe++x1jRFSx65qyMki843r3L9NCCFEup3fDihFqvwGtHrpPhg6jJdtVBI0caw53fXIXB88fpE50HVYPW02sMdbXwxLFkMxXIUpv//791K5d270cGlr8j0yjRo3i999/Z/Pmzd4cmt+QiEoAy3IGyErcbCs7Fb4cBYeczTKa3gV3vQVhsd4ZoAdEhqo1XzOLzHyV4KunhBl0XMqxkmNRf/GVsgNCBD9jRBQR0bG+HoYQorJQFNi+AL5/Lk+/gUVQ90Zfj0wIj7E77Ny38j62/L2FmNAYVg9bTZ3oOr4eligBq7PhlmS+ClFyUVFRREdHl3j90aNHs2rVKjZu3EidOrnvjQkJCVgsFtLS0vJlv6akpJCQkOBeZ/v27fn2l5KS4r7PX8nPOQEs2x18LUEM/e/t8F5nNfCqC4G+s2DwEr8OvELesgOF13yNk+Crx7gC+dmXZb5GhErwVQghhBDllJMG/3c/rB7n7Ddwu7PfgAReRfBQFIWn1jzFFwe+IEQXQtLQJFrUaOHrYYkSsjnLDuh1EnwVwtMURWH06NGsXLmS9evX06BBg3z3t2nTBoPBwLp169y3HTp0iJMnT9KhQwcAOnTowL59+zh79qx7nbVr1xIdHX1F+QN/IpmvASz3kvAiAmMOB2x9C9ZNA4cNqjSAez6CWq0rZIzlFV1UzddsNfhaTcoOeIzRWT/48pqvYQZ5qxBCCCFEOZzaCSuGQ9pJtd9Azxeh3WN+129AiPKauWUm83bMA+B/A/5H1/pdfTsgUSrusgNSAkUIjxs1ahTLli3jyy+/JCoqyl2jNSYmhrCwMGJiYhg5ciSJiYnExcURHR3NE088QYcOHWjfvj0APXv2pFmzZtx///3MnDmT5ORknn/+eUaNGlWicge+IhGVAJZtLqbma9YFSHoM/vpeXW4+EO58E4wlTwf3tUhX8NWcP/PV7oBLOWpANk4abnmMK5DvqiecbVafY8l8FUIIIUSZKApsewfWTg6IfgNClMfSvUt5Zt0zAMzpOYfBzQf7eESitKwOKTsghLe8++67AHTt2jXf7YsWLWL48OEAvP7662i1WgYNGoTZbKZXr16888477nV1Oh2rVq3i8ccfp0OHDkRERPDggw8ybdq0inoYZSLB1wBWZM3XEz/DipGQcRp0odDnVWgzPOCyC6IKqfma6VzUaiA2zFDRwwpartqu7sxXawmyq4UQlY7D4SAtLa3E68fGxqKVDBIhKp8A7DcgRFn9cPQHhn85HIDE9omM7TDWtwMSZWJ3qGUHDFJ2QAiPUxSl2HWMRiPz5s1j3rx5ha5Tr149vv32W08Ozesk+BrACiw74HDA5jnw43RQ7FC1kVpmICEw6wxFFVJ2INOZCFslPASt/CrpMWEGV81XV+ar6xyTtwohRK60tDTmrNqFMSKq2HVNWRkk3nE9cXFxFTAyIYTf+Hs7LB8B6afUfgO9psON/w64RAAhSmJ38m4GfjYQm8PG4OaDea3na74ekigjabglhPAGiagEsCsabmWegy8ehqM/qsvXDYHb50BopI9GWH6usgPpV2S+qh+GVaXeq0e5Ml9NVjtWuwOLs+C8ZL4KIS5njIgiIjrW18MQQvgbhwN+nqv2G1DsEHe1mghQs5WvRyaEV5xIO0GfpX3IsGTQtX5XlvRfglYjV3sEKlfNV71OXkMhhOdI8DWAZZnzdKI/thE+/zdkpoA+DG6fBa2HBXx2QbTRWXbgspqvrszXuAgJvnqSK8iabbG7s1/V2+WtQgghhBDFyLoAKx+Fw2vV5RaD4I43AqrfgBClkZqTSu+lvUnOTKZFjRasHLKSUL30owhkVmfyiV4yX4UQHiQRlQCWY7GjxUGX0wth2wJQHFC9iZpdUKOpr4fnEa6yAyarA6vdgcH5C6Qr+FpVmm15lNGQW/PV1XRLr9UQopdffoUQQghRhLz9BvRGtd/ADQ8GfCKAEIXJseZw1yd3cfD8QepE12H1sNXEGmN9PSxRTja7ZL5WNIfDQWpqKgZDyXq5SC8BEYgk+BrAdNkpfGyYzk0n9qs3XH8f9HkNQsJ9OzAPigjNPUUzTDZ3pmumVZ3IS+arZ7kyX3Ms9jxlLaTkgBBCCCEK4XDA5tnOfgOOgO83IERJ2B127lt5H1v+3kJMaAyrh62mTnQdXw9LeICr7IBBMl8rTFZWFm+u3kN4VGyx60ovARGoJPgaqI6sZ8LxfxOjS8OqC8Nw1xvQaqivR+VxBp2WMIOOHKudzLzBV2cJWAm+epar4VZOnrIDUnJACCGEEAXKPAtfPJKn38BQuH12QPcbEKI4iqIwZs0YvjjwBSG6EJKGJtGihvzYECysDrXsgDTcqlhhkdJLQAQ3iaoEGrsNNsyATbOJQeGAoy7JPebTrdUtvh6Z10QZ9eRY7aSbcuu+usoOVJOGWx4V5gy0ZlvzBF9DJfNVCCGEEJc5+pPa6NXdb2A2XD/M16MSwute+/k13t7xNgBL+i+ha/2uvh2Q8Ch35quUHRBCeJAEXwPJpX/UplonfwZgtbEPY9KG8G61Rj4emHdFGfWczTCTYbK5b8stOyA1Xz0pb+ZrlpQdEEIIIcTlHHb4aSb89CqgQPWmzn4DTXw9MiG87uO9HzPhhwkAzOk5hyEthvh4RMLTrM6ar5L5KoTwJAm+Boq/1qqXdeWkQkgU3PkGs76vhpmsoL8sPNKoFt7ONOcNvqr/lbIDnuWu+Wq1uRtuBfv5JYQQQogSykhWEwGOb1KXg7DfgBCF+eHoD4z4cgQAie0TGdthrI9HJLzB7iw7oNdJ8FUI4TkSVfF3diusfxG2vKkuJ1ynZhdUbUj2qnUARAR5cCzaqD6+jLxlB5xx2KpSdsCjjHkzX82S+SqEEEIIpyPr1USArHNgiIA7XodWkvUnKofdybsZ+NlAbA4bQ5oP4bWer/l6SMJLXJmvBq2UHRBCeE5wR+0CXdrfsOIhOLVdXb7xYej5EhiMAO6anGFBHhyLcgdf1WCg1e4g26b+EllVMl89yhVozbbYybGq51ewB/eFEEIIUYQ8/QZAgfgWaiJAkJe9EsLlRNoJ+iztQ4Ylg671u7K4/2K0GgnMBSubq+yAZL4KITxIoir+6uC3kPQ4mNIgNAb6vQXN+uVbJdtZkzMiyBsiRYaqp6mr7EBatpoBq9FAbLgEX8vCbrdjtVqvuD1MZ6d2lI5og4LdaqF2lI4aEVpMJpNHj2+1WtHr9ZhMJux2u0f3LbzPX14/nU6HXq9Ho5HJsRBCeMVl/QZoMwJ6zwBDmG/HJYKCoijYbDafzSVKMp9JM6Ux4vMRhCqh3HbVbXzc/2MUm4LJ5tm5sSgbb8xJQ7BRO0pHlRClRN+BZD4qhCgJCb76G5sFfpgC2+apy7VugLsXQlyDfKtZbA73JRHBXpMzylnzNd1ZdiA1ywJAbJhBCqGXQWZmJqdOnUJRlCvuC7E5mNKtBjqthogQE1O61SAyVMOxY8c8OgZFUUhISODvv/+WiUoA8qfXLzw8nJo1axISIj/ECCGER/35Pax8NLffwF1vQotBvh6VCBIWi4UzZ86QnZ3tszEUN59RFIWUrBTGNxuPTqsjITKBC6cvcIELPhitKIg35qTXx1m5plsNIkMp8XcgmY8KIYoT3FG7QHPxuFpm4J+d6nL7/0CPqaC/8k3c1QwJgr8m5+VlB1Kz1eCrNNsqPbvdzqlTpwgPD6d69epXTFLMVjtcyEKr1RBjNGDMtlAlIoQaUUaPjsPhcJCZmUlkZCRaqacUcPzh9VMUBYvFwrlz5zh27BiNGjWSc0kIITzBboV10+DnuepyzVZw9yKo2tC34xJBw+FwcOzYMXQ6HbVq1SIkJMQnP+YWNZ9RFIWTl04SFRlFDDFcXeVqjAbPzodF+XljTno2w8TFrJJ9B5L5qBCipCT46i/2fwVfjgbzJTDGQv93oUnfQlfPcpYcCNFpMeiC+w3eXXbAFXzNUjNgpd5r6VmtVhRFoXr16oSFXXnJoFbvQKO3Ahq0BgMaPYSGGjEaPR98tVgsGI1GmaAEIH95/cLCwjAYDJw4ccI9HiGEEOVweb+Bmx6Fni+CPtS34xJBxWKx4HA4qFu3LuHh4T4bR2HzGUVR+Dv9bzIcGWj0GhpVbURUaJTPxikK5405qd6koNFDSEhoieaWMh8VQpSEBF99zWaG75+H7e+ry3VuVMsMxF5V5Gaueq/hQV7vFSDaWXYgw1l24EKWZL6WV2HZBa4qDgoKdofivE3KAgj/JcF7IYTwkCv6DbwNze7y9ahEEPPXz/CUrBTOZp0FoEGVBhJ4rWTchdlK8R3IX89lIYT/kOCrL104AitGwJk96nLHp+DWF0BnKHbTLLNadiDcEPzB1yvKDriDr8U/T6J0tHlq6NrcwVdfjUYIIYQQXmezwA+TYds76nKtG+CeRVClvk+HJYQvXMi+wKn0UwDUja5LXFicj0ckKpqrL4Z8BRJCeJIEX33l98/hq6fAkgFhcTDgPbi2Z4k3z3bWfA0PDf6XMNIZfM00XxZ8DZfMV09wOBykpaUB6mQj/WI6CpCj12KxOYjChMbi2ec6Ojrao/sTQgghRBlcPA7LR8Dp39Tl9qOgx5QC+w0I4U1556MV5fL5aLo5neNpxwGIj4gnPjK+Qscj/IOrJ7Fc/CeE8KTgj9z5G2sOrJkIOxepy1d1gEEfQkztUu3GVXYgIsibbQFEucsO5A++Vo2ULwaekJaWxpxVuzBGqJdUXcg041DUcgMORSEmXE+IznPnmSkrgzF9W6HXB87bz/Hjx2nQoAG7du2idevWvh4OAAcPHmT48OHs3r2bJk2asHv37go79tSpU/niiy/Ys2dPhR1TCCGEh5Wy34AQ3nT5fNTbLp+PZluzOZx6GAWFKsYq1ImuUyHjKA2Zj+Y3ZcoUkpKS2LBhg1f2r5HcVyGEBwVO9CMYnP8Llg+HlN8BDXRKhK7Pgq70L0OWM/M1rFIEX9XnJ/3ymq+S+eoxxogoIqJjAcjWmHEo7mpHRIQbCNH79jwbPnw4ixcvZsaMGTzzzDPu25OSkhgwYID78qDKZPLkyURERHDo0CEiIyMr9Nj//e9/efDBByv0mEIIITzEaoK1L+TpN3CTs99AXd+OS1R6eeejFclit/DXhb9wKA6iQqJoUKVBgf0RZD56JV/OR59++mlGjRrl8f26M189vmchRGUmlaEryp7P4L0uauA1vBrc9zl0n1SmwCtAjjvzNfjj51GhuWUHFEUhNUsNwkrDLe+4fK5ZWHOuimY0Gnn11Ve5ePGir4fiMRaLpczbHjlyhFtuuYV69epRtWpVrx8vr8jISOLipAaaEEIEnAtH4MPbcgOvHZ+CEd9K4FVUWnbFzuGLh7E6rITpw2gY1xCtpvCvyDIfzc/X89GSHrM0FGfLLT/5CiSECBISfPU2SzZ8OQpWPgLWLKjfCR7fAtd0L9du3Q23KkHNV1fZAUVRM34vZkvDLW+6Mvjqm3FcrkePHiQkJDBjxoxC15kyZcoVl2G98cYb1K9f3708fPhw+vfvz/Tp04mPjyc2NpZp06Zhs9kYN24ccXFx1KlTh0WLFl2x/4MHD3LzzTdjNBpp0aIFP/30U777f//9d/r06UNkZCTx8fHcf//9nD9/3n1/165dGT16NGPGjKFatWr06tWrwMfhcDiYNm0aderUITQ0lNatW7NmzRr3/RqNhp07dzJt2jQ0Gg1TpkwpcD+FHa+ocb7//vvUqlULh8ORb1/9+vXjoYceAtSyA506dcp3/wcffEDTpk0xGo00adKEd955x33f3XffzejRo93LY8aMQaPRcPDgQUCdhEdERPDDDz8AsGLFClq2bElYWBhVq1alR48eZGVlFfgYg4nD4SA1NbVU/1yvU2m3vfz1FUJUAr9/riYCJO9V+w38azncNq1EjV6FCEaKonDGfAaTzUSILoRGVRuh1xb93Urmo/4zH50yZQo33HBDvvs9MR/dtOFHAL5K+qJSzkfLQ+ajQhQu+CN3vnT2oFpm4NwBQANdJkCX8aAt/yXclanmq9GgRa/VYHMopGVbSMtRM1+rSuarV6j1jZQ8y/5Bp9Mxffp0/vWvf/Hkk09Sp07Za3GtX7+eOnXqsHHjRrZs2cLIkSP5+eef6dy5M7/88gufffYZjz76KLfddlu+44wbN4433niDZs2aMWfOHO68806OHTtG1apVSUtL49Zbb+Xf//43r7/+Ojk5OUyYMIHBgwezfv169z4WL17M448/zpYtWwod35tvvsns2bN57733uP7661m4cCF33XUXf/zxB40aNeLMmTP06NGD3r178/TTTxd5mdflxytunPfccw9PPPEEP/74I927qz8SpaamsmbNGr799tsCj7F06VImTZrE22+/zfXXX8+uXbt4+OGHiYiI4MEHH6RLly6899577vV/+uknqlWrxoYNG2jSpAk7duzAarVy8803c+bMGe69915mzpzJgAEDyMjIYNOmTZXiUr7S1rszZWWQeMf1xMXFlWpbU1YGT/RqUd7hCiECxRX9Bm6GQR+Uut+AEMFF4UT6CQgDnUZHo7hGhOiK/24h89Hgn4+2ubEdp1OSeWTEA5VyPloepZ2PJt5xPVFRFVPnWQhfk+CrNygK7F4K3zwNthyIjIeBC+DqLh47RHYlqvmq0WiINOpJy7ZyMjUbRQENCrFS89Ur/LXsAMCAAQNo3bo1kydP5sMPPyzzfuLi4pg7dy5arZbGjRszc+ZMsrOzefbZZwGYOHEir7zyCps3b2bo0KHu7UaPHs2gQYMAePfdd1mzZg0ffvgh48ePd0/0pk+f7l5/4cKF1K1blz///JNrr70WgEaNGjFz5swixzdr1iwmTJjgPvarr77Kjz/+yBtvvMG8efNISEhAr9cTGRlJQkJCkfu6/HgvvfRSsePs06cPy5Ytc092V6xYQbVq1ejWrVuBx5g8eTKzZ89m4MCBADRo0ID9+/fz3nvv8eCDD9K1a1eeeuopzp07h16vZ//+/bzwwgts2LCBxx57jA0bNnDjjTcSHh7OwYMHsdlsDBw4kHr16gHQsmXLIh9jMClPvTtf1coTQvixy/sNdH4aujxT5rJXQgQHhQxLBpdMGmLDYmlYpSFhhrASby3z0eCej4aGhXH+bEqlno+Wh8xHhSiYlB3wNHMmrHxMLTVgy4Gru8Fjmz0aeIXc4GtlqPkKuU23TlzIBiBcDzqt/wQFg8nlz6q/Pcuvvvoqixcv5sCBA2XeR/PmzdFqc9/+4uPj802odDodVatW5ezZs/m269Chg/v/9Xo9bdu2dY9jz549/Pjjj0RGRrr/NWnSBFDrYbm0adOmyLGlp6dz+vRpOnbsmO/2jh07lukxX368koxz2LBhfP7555jNZkDNJBg6dGi+58wlKyuLI0eOMHLkyHz7fOmll9z7a9GiBXFxcfz0009s2rSJ66+/njvuuMN9mdxPP/1E165dAWjVqhXdu3enZcuW3HPPPSxYsCCo6qoJIUSFydtvIKI63P8F3Pq8BF5FpZdpySLLon6nqBFSg8iQ0jeKkvlo6QTafPTaZi3o0rWbzEeFEB4jsy9PSv4dVoyA83+CRgvdnoVb/gsFfECUV5ZZLTsQHhr8ma8AUaEGIMcdfI2U8mRe4681X106d+5Mr169mDhxIsOHD893n1arveJyIKvVesU+DIb8J5BGoynwttLUIcrMzOTOO+/k1VdfveK+mjVruv8/IiKixPv0hMuPV5Jx3nnnnSiKwjfffMONN97Ipk2beP311wvcf2ZmJgALFiygXbt2+e7T6dT3J41GQ+fOndmwYQOhoaF07dqV6667DrPZzO+//87PP//M008/7d5m7dq1/Pzzz3z//fe89dZbPPfcc/zyyy80aNCgfE+GEEJUBpZsWD0Odn2sLtfvpJYZiCo6M02IyiDHmk26OR2AWlG1iNKX7ZJnmY+WTiDNRxVF3SZp1Wr+2P2rzEeFEB4hwVdPUBTY+RGseQZsJoiqCYM+hPodi920rLKtzoZbhsoRfI10Zr4eP68WOY+UM9drNHlyXdXAq59FX4FXXnmF1q1b07hx43y3V69eneTkZBRFcZdL2L17t8eOu23bNjp37gyAzWZj586d7sL9N9xwA59//jn169dHry/7CRodHU2tWrXYsmULXbrkZsxv2bKFm266qXwPoITjNBqNDBw4kKVLl3L48GEaN258RUMDl/j4eGrVqsXRo0cZNmxYocft0qULCxYsIDQ0lJdffhmtVkvnzp157bXXMJvN+TIrNBoNHTt2pGPHjkyaNIl69eqxcuVKEhMTy/fghRAi2J094Ow3cBDQQNdnoPM4j/QbECLQme1m0kxpAESEhFM9vHq59ifz0bLz5/nomSw1cK7RamU+KoTwGAlhlZcpHVaNUTvIAlxzGwyYDxHVvHrYbHfma+V4CaNdwdcLzuCrQYqde5IpK8P9/zlmGznOshZarYYsxeS1Y5VVy5YtGTZsGHPnzs13e9euXTl37hwzZ87k7rvvZs2aNaxevZro6OhyHxNg3rx5NGrUiKZNm/L6669z8eJFd8fVUaNGsWDBAu69917Gjx9PXFwchw8f5tNPP+WDDz5w/+peEuPGjWPy5Mk0bNiQ1q1bs2jRInbv3s3SpUvL/RhKOs5hw4Zxxx138Mcff3DfffcVuc+pU6fy5JNPEhMTQ+/evTGbzfz6669cvHjRPUHt2rUrY8eOJSQkhFtuucV929NPP82NN97ozoj45ZdfWLduHT179qRGjRr88ssvnDt3jqZNm5b7sQshRNAqqN/AoA+gQWdfj0yIEvPEHLEwNsXGhewLKIpCmD4Ug738P0jIfLTs/Hk+qmRlsHfXr6z4bSt33d5H5qNCCI+oHJE7bzmzR80uSD0KGh10nwQ3P+mVMgOXy6p0NV/VS3BOpkrZAU+LjY0l8Y7r3cvJ6TlcyLAAYNBruDbeMxPFvKKjo92XB5XVtGnT+Oyzz/Ld1rRpU9555x2mT5/Oiy++yKBBg3j66ad5//33y3Usl1deeYVXXnmF3bt3c8011/DVV19RrZr6Q4srO2DChAn07NkTs9lMvXr16N27d4G1qYry5JNPcunSJf773/9y9uxZmjVrxldffUWjRo3K/RhKOs5bb72VuLg4Dh06xL/+9a8i9/nvf/+b8PBwXnvtNcaNG0dERAQtW7ZkzJgx7nVatmxJbGws1157rbsbbteuXbHb7e76WqCeGxs3buSNN94gPT2devXqMXv2bPr06VPux15RHA4HaWlppdomNjbWK2MRQlQC5kz45r+w91N1+epuaqPXyPJl9QlRkS6fj3qS2Wbmrwt/YXWEExkSScO4hmg1WpmPFqOyzkcVBSIjo/h5y2bmz3srYOejQgj/Ujkid56mKLDjA/juWbBbILoO3L0QrmpX/LYekm1xZr6GVI7LyFwNt1yNxqTsgOdotVri4uLcy1a9CZtezXY1GnTExZWtFlZRSlO7CuCjjz664rb69eu7C/Dn9dhjj/HYY4/lu83VNbawfW3YsOGK244fP57vWK7aXffee2+h42zUqBFffPFFofcXdJyCaLVaJk+ezOTJkwtdpySXrxV2vOLG6RrD6dOnC7xv8uTJjB07Nt9t//rXv4qcFGu1WlJTU/Pd1rp16ytqojVt2pQ1a9YUOTZ/l5aWxpxVuzBGlOxvx5SV4bUvnEKIIJf8u5oIcOEvZ7+B5+CWxApJBBDCky6fj3qKzWHj4PmDhMeEE6YPo3G1xui16hcJmY8Wzd/no1OmTGHSpEmkp6e7b/PIfFSBqxs1JumrVUQaJeNHCOEZEsIqLdMl+OoJ2P+lunxtH+j/DoR7frJQFFcQsrIEXyMvK68gZQe8R6vJ+//+V+9ViEBgjIgiIjrW18MQQgSrK/oN1IK7P4R6N/t6ZEL4DYfDweHUw5hsJkJ0ITSq2sgdeBWiMK5vmRr5HiSE8CD59CmNf3bC8hGQdgK0BrhtKrT/j0/awWebnWUHKknN16jLfnWUsgPekzfgqpU5hxBCCOFfCuw38B5EVPXpsITwJ4qicDTtKJmWTHQaHY3iGhGiC/H1sEQAUJAkHyGE51WOyF15KQr8Mh++fwEcVoi9Cu7+COq08dmQsipp2QEXCb56T95feXUSfRVCCCH8x+X9BnpMhg5PSJkBIfJQFIW/0/8mzZSGBg3XxF1DmCHM18MSAcJVgUASX4UQniTB1+Jkp8KXo+HQN+py0zvhrrchLNZnQ1IUxd2NPrzSNNy6LPiql18kvUXKDgghhBB+5vJ+AzF11X4DdW/y9ciE8DspWSmczToLQIMqDYgK9Xz/AhG83GUHqLzfg0rbPDY2NrbUDd2EqGwqR+SurP7eAStGwKW/QRcCPV+Gmx72+c9gFrsDm0P9WAgPlcxXUXqXNznKS8oOiEBS1LkshBBBIScNvn4yt99A477Qb16F9xsQwtO88Rl+IfsCp9JPAVA3ui5xYfJ3IkqpDJmvwTYfLU3zWFfjWG80zBMimEjwtSAOB2x9C9ZNA4cNqjSAez6CWq19PTIgt94rQLihsgRf80dbIyT4WiY6nXq+WCwWwsIKvvwqf/BVoq/Cv2VnZwNgMMibghAiCF3Rb2AatH/c54kAQpSH6zM7Ozu70PloWaSb0zmedhyA+Ih44iPjPbZvUXm4ar6W5l02GOej0jxWCM+S4Ovlsi5A0uPw13fqcvOBcOebYIz27bjyyLaqwdcQvRa9rnKk90fmaSwWG2ZAp7H5cDSBS6/XEx4ezrlz5zAYDAVeHmK12FBsFgDsNg0mk+e/4DkcDiwWCyaTSS5RCUD+8PopikJ2djZnz54lNjbW/cOCEEIEBUWBbe/C2knOfgP14J5FUNt3/QaE8BSdTkdsbCxnz6qlAcLDw8vdWT7HmsPRi0dRUIgJjaFaSDVMJlOR2/jDfEaUjzdeQ7vVgqIomM0mFHvR80uZjwohSkqCr3md2AorHoKM06ALhT6vQJsRfpddkG1WA48RlaTZFuQvOxAX8f/s3Xd4FFUXwOHfluymNyAhgUBC710pShUFKQKioNJFsICKKGKlqAgoYqVIFwT5RIpIU6SL9CZIh9CkhvS6bb4/ll0IBFLINjjv8+SBnZ1yZ2fLmTN3zvUCMlzXGA+mUqmIiIggNjaW06dP5ziP0WzhcnIWAFk+WlK8C/8KrqIoZGRk4OPjc9fBtnA+dzp+wcHBFC9e3CHrzm+9K1t7hBDirqTHw68D4MgK6+PKT8AT37p0vAEhCpvtt9uWgL0bJouJi6kXMVvMeGu98fXz5VT8qVyXc6d4RhSMI47h5cQMFAU0ad55HnzYkfGoEOLeIMlXsJYZ2PwlrB0FihmKlLOWGShe3dUty1HafTbYFmQvOxDqp3NhSzyfTqejfPnyGAyGHJ+/kJjBy79uA+C1R8rToXKJQm+D0Whk48aNNGnS5J66Ped+4S7Hz8vLy6E9DPJT7wqu17wSQogCO7vd2hHANt5Aq0/hgRfcriOAEHfL1iEgLCwMo9FY4PUkZiby3MLnOJlwkgpFKvDjkz8SqM/bHYvuEs+IgnPEMXxh/HpQ4OeXGlLET5/r/I6OR4UQ94b7J3t3O6lXYHF/OLHW+rhGV2g7HvT+rm3XHaQbrD1ffe+jnq83lh2Q5OvdU6vVeHt75/hcgL+K/1KsCX6tl/62890NjUaDyWTC29tbgl0P5GnH725GbJV6V0IIp3Dz8QaEcBSNRlPgxFWGMYOnFj3F5nObKRlYkhmdZxAWGJavbXtSPCNuVdjH0GJR+C/5Wkcnbx+8vT37vPNuYmAhROFyi+TrhAkT+Pzzz7l48SI1a9bk22+/5cEHH7zt/AsWLODDDz/k1KlTlC9fnrFjx9KmTZv8bzh2Eyx8AVIvgtYH2nwOtbu7fe8C24Bbvnq3OHxOoVGr8NNpSDOYJfnqYDcm9f3090+CX9y7ZMRWIa7Lb8x1P3FZPJqeAD8NgWN/WB+74XgDQrgbs8VM98Xd2Xx2M8HewazqtoqSgSVd3Szh4YwWi/3/Go175wTyQmJg4a7ux3jU5dm7//3vfwwePJjJkydTv359vvrqK1q1asWRI0cIC7v1yuXff//Ns88+y+jRo2nXrh3z5s2jY8eO7N69m2rVquV5u6ptk+DwFFAsULQidPkBwioX5q45TJrh/qv5CtbSA2kGM6G+Osj5jnlRCLy1199XPvdRaQvh/qQHqxB3J78x1/3EVfEogOanp0ATd228gbFQt7fbdwQQwpUURWHQqkEsOrQInUbHkq5LqBpW1dXNEvcAs0Wx/9/LAT1ACxrLSgws7iX3azzq8szK+PHj6devH3369AFg8uTJLF++nBkzZvDOO+/cMv/XX39N69atGTJkCAAff/wxq1ev5rvvvmPy5Ml53q5m20QIVEOt7tDmM9D5sfNUPHGpWYWzYw6081QC4JiyA876Qbhx2bzy99ZCsnXALUumhfj4+HzdXnK3t1E4+8fSFT/OAGq1Cm8vNZlGS54S/AXZnm25/BzDu32vAU5dzpOOfX6X8/PzA64fQ2e1U67eC3F38htz3U9cFY8CqNIuQ0zFa+MNVOO/xAz2n0u8210SDmYymdl3VYXm30totfdXhwhXW3x4CXP+2YUvjRj84GAyUiuw6sCFfK9HjqHnK+xjmGE02/+vvU3P17s57y1oLCsxsLiX3K/xqEuTrwaDgV27dvHuu+/ap6nValq2bMmWLVtyXGbLli0MHjw427RWrVqxZMmSHOfPysoiK+t6QjUpKQmA8+la4hoMRSndCv49CsDwXw+y+2xSjuvR6P3s/zdnpeW+c05YLj0kjT17sh/CkJAQ+/8TEhLyvD3bcgkJCUz6fQ86b99clzFkpvNyq9qEhITka7mcls2Tq6fJupKKJTmEs2fP8v603/D2y1tt3hu3B+772rhyOds+Aqjiz5KVaeLMsSA0CX45Lns3r4u/v3++jmFhvNcApy7nScc+v8v1e6Q6cXFx/PPPP0xds9+p7UxKuJrtO/12MtNTOX36NMnJySQkJHDp3Cm8fXN/r1mX88r3cjcuCzh1uYLs45kzKuLi4jhz5ozDXxtZrnCXsy37n976+UlKSiIw8Prt6Xq9Hr3+1gFCChJz3S+cEY/C7WPSf30bcqX+cLhghAt7WHskjnGrj+W4DmfHozcu6+zl8rusy5bbucYz2unmy924bF6WC6I7ANN+ucRM/R93tT05hvfAcpuX5nm5G5e93fbUKti/b98tNyEUxnlvQWNZd42B73Y5f39/4uPjuWDS4heQ+zm6p8VrnnJuUNDlJB7NB8WF/vvvPwVQ/v7772zThwwZojz44IM5LuPl5aXMmzcv27QJEyYoYWFhOc4/fPhwBZA/+ZM/+ZM/+ZM/+bvn/4YPH15oMdf9whnxqKJITCp/8id/8id/8id/98efxKO3cnnZAUd79913s/VMiI+PJyYmhgMHDhAUFOTClomCSklJoUqVKhw8eJCAgNxvvRDuR46hZ5Pj5/nkGHq+pKQkqlWrRmxsbLZbC3PqZSDcg8Sk9xb5HvV8cgw9nxxDzyfH0LNJPJp3Lk2+Fi1aFI1Gw6VLl7JNv3TpEsWLF89xmeLFi+dr/tt1d46KisrWLVp4juTkZABKlCghx9BDyTH0bHL8PJ8cQ89nO26hoaF5OoYFibnuF86IR0Fi0nuNfI96PjmGnk+OoeeTY+jZJB7Nu8Ifwi8fdDoddevWZc2aNfZpFouFNWvW0LBhwxyXadiwYbb5AVavXn3b+YUQQggh7ncFibnuFxKPCiGEEEI43v0cj7q87MDgwYPp1asX9erV48EHH+Srr74iLS3NPvJZz549KVGiBKNHjwbg9ddfp2nTpnzxxRe0bduW+fPns3PnTqZMmeLK3RBCCCGEcGu5xVz3M4lHhRBCCCEc736NR12efO3atStXrlxh2LBhXLx4kVq1arFq1SrCw8MBOHPmDGr19Q66jRo1Yt68eXzwwQe89957lC9fniVLllCtWrU8bU+v1zN8+HCpQeHB5Bh6PjmGnk2On+eTY+j5CnIMc4u57mfOjkdBPoeeTo6f55Nj6PnkGHo+OYaeTeLRvFMpiqK4uhFCCCGEEEIIIYQQQghxr3FpzVchhBBCCCGEEEIIIYS4V0nyVQghhBBCCCGEEEIIIRxAkq9CCCGEEEIIIYQQQgjhAJJ8FUIIIYQQQgghhBBCCAe4J5OvEyZMIDo6Gm9vb+rXr8/27dvvOP+CBQuoVKkS3t7eVK9enRUrVjippeJ28nMMp06dSuPGjQkJCSEkJISWLVvmesyF4+X3c2gzf/58VCoVHTt2dGwDxR3l9/glJiYyYMAAIiIi0Ov1VKhQQb5LXSy/x/Crr76iYsWK+Pj4EBUVxRtvvEFmZqaTWitutHHjRtq3b09kZCQqlYolS5bkusz69eupU6cOer2ecuXKMWvWLIe3U+ROYlLPJvGo55N41PNJTOrZJB71bBKTFiLlHjN//nxFp9MpM2bMUP7991+lX79+SnBwsHLp0qUc59+8ebOi0WiUzz77TDl48KDywQcfKF5eXsr+/fud3HJhk99j+NxzzykTJkxQ9uzZoxw6dEjp3bu3EhQUpJw7d87JLRc2+T2GNrGxsUqJEiWUxo0bKx06dHBOY8Ut8nv8srKylHr16ilt2rRR/vrrLyU2NlZZv369snfvXie3XNjk9xjOnTtX0ev1yty5c5XY2Fjl999/VyIiIpQ33njDyS0XiqIoK1asUN5//31l0aJFCqAsXrz4jvOfPHlS8fX1VQYPHqwcPHhQ+fbbbxWNRqOsWrXKOQ0WOZKY1LNJPOr5JB71fBKTejaJRz2fxKSF555Lvj744IPKgAED7I/NZrMSGRmpjB49Osf5u3TporRt2zbbtPr16ysvvviiQ9spbi+/x/BmJpNJCQgIUH744QdHNVHkoiDH0GQyKY0aNVKmTZum9OrVS4JdF8rv8Zs0aZJSpkwZxWAwOKuJIhf5PYYDBgxQWrRokW3a4MGDlYceesih7RS5y0ug+/bbbytVq1bNNq1r165Kq1atHNgykRuJST2bxKOeT+JRzycxqWeTePTeIjHp3bmnyg4YDAZ27dpFy5Yt7dPUajUtW7Zky5YtOS6zZcuWbPMDtGrV6rbzC8cqyDG8WXp6OkajkdDQUEc1U9xBQY/hRx99RFhYGH379nVGM8VtFOT4LV26lIYNGzJgwADCw8OpVq0an376KWaz2VnNFjcoyDFs1KgRu3btst8KdvLkSVasWEGbNm2c0mZxdySWcT8Sk3o2iUc9n8Sjnk9iUs8m8ej9SWKZ29O6ugGFKS4uDrPZTHh4eLbp4eHhHD58OMdlLl68mOP8Fy9edFg7xe0V5BjebOjQoURGRt7yoRfOUZBj+NdffzF9+nT27t3rhBaKOynI8Tt58iRr166lW7durFixguPHj/PKK69gNBoZPny4M5otblCQY/jcc88RFxfHww8/jKIomEwmXnrpJd577z1nNFncpdvFMsnJyWRkZODj4+Oilt2/JCb1bBKPej6JRz2fxKSeTeLR+5PEpLd3T/V8FWLMmDHMnz+fxYsX4+3t7ermiDxISUmhR48eTJ06laJFi7q6OaIALBYLYWFhTJkyhbp169K1a1fef/99Jk+e7OqmiTxav349n376KRMnTmT37t0sWrSI5cuX8/HHH7u6aUII4XEkHvU8Eo/eGyQm9WwSj4p72T3V87Vo0aJoNBouXbqUbfqlS5coXrx4jssUL148X/MLxyrIMbQZN24cY8aM4c8//6RGjRqObKa4g/wewxMnTnDq1Cnat29vn2axWADQarUcOXKEsmXLOrbRwq4gn8GIiAi8vLzQaDT2aZUrV+bixYsYDAZ0Op1D2yyyK8gx/PDDD+nRowcvvPACANWrVyctLY3+/fvz/vvvo1bLtVp3drtYJjAw8L7uYeBKEpN6NolHPZ/Eo55PYlLPJvHo/Uli0tu7p969Op2OunXrsmbNGvs0i8XCmjVraNiwYY7LNGzYMNv8AKtXr77t/MKxCnIMAT777DM+/vhjVq1aRb169ZzRVHEb+T2GlSpVYv/+/ezdu9f+98QTT9C8eXP27t1LVFSUM5t/3yvIZ/Chhx7i+PHj9pMUgKNHjxIRESFBrgsU5Bimp6ffEtDaTlwURXFcY0WhkFjG/UhM6tkkHvV8Eo96PolJPZvEo/cniWXuwLXjfRW++fPnK3q9Xpk1a5Zy8OBBpX///kpwcLBy8eJFRVEUpUePHso777xjn3/z5s2KVqtVxo0bpxw6dEgZPny44uXlpezfv99Vu3Dfy+8xHDNmjKLT6ZRffvlFuXDhgv0vJSXFVbtw38vvMbyZjC7rWvk9fmfOnFECAgKUgQMHKkeOHFGWLVumhIWFKZ988omrduG+l99jOHz4cCUgIED56aeflJMnTyp//PGHUrZsWaVLly6u2oX7WkpKirJnzx5lz549CqCMHz9e2bNnj3L69GlFURTlnXfeUXr06GGf/+TJk4qvr68yZMgQ5dChQ8qECRMUjUajrFq1ylW7IBSJST2dxKOeT+JRzycxqWeTeNTzSUxaeO655KuiKMq3336rlCpVStHpdMqDDz6obN261f5c06ZNlV69emWb/+eff1YqVKig6HQ6pWrVqsry5cud3GJxs/wcw9KlSyvALX/Dhw93fsOFXX4/hzeSYNf18nv8/v77b6V+/fqKXq9XypQpo4waNUoxmUxObrW4UX6OodFoVEaMGKGULVtW8fb2VqKiopRXXnlFSUhIcH7DhbJu3bocf9dsx6xXr15K06ZNb1mmVq1aik6nU8qUKaPMnDnT6e0Wt5KY1LNJPOr5JB71fBKTejaJRz2bxKSFR6Uo0n9bCCGEEEIIIYQQQgghCts9VfNVCCGEEEIIIYQQQggh3IUkX4UQQgghhBBCCCGEEMIBJPkqhBBCCCGEEEIIIYQQDiDJVyGEEEIIIYQQQgghhHAASb4KIYQQQgghhBBCCCGEA0jyVQghhBBCCCGEEEIIIRxAkq9CCCGEEEIIIYQQQgjhAJJ8FUIIIYQQQgghhBBCCAeQ5KsQQuRB79696dixo/1xs2bNGDRokNPbsX79elQqFYmJiU7fthBCCCGEcC2JSYUQwvNI8lUI4bF69+6NSqVCpVKh0+koV64cH330ESaTyeHbXrRoER9//HGe5nV2cBodHW1/XXx9falevTrTpk1zyraFEEIIIe43EpPmTGJSIYSwkuSrEMKjtW7dmgsXLnDs2DHefPNNRowYweeff57jvAaDodC2GxoaSkBAQKGtr7B99NFHXLhwgQMHDtC9e3f69evHypUrXd0sIYQQQoh7ksSkOZOYVAghJPkqhPBwer2e4sWLU7p0aV5++WVatmzJ0qVLgeu3ZY0aNYrIyEgqVqwIwNmzZ+nSpQvBwcGEhobSoUMHTp06ZV+n2Wxm8ODBBAcHU6RIEd5++20URcm23Ztv8crKymLo0KFERUWh1+spV64c06dP59SpUzRv3hyAkJAQVCoVvXv3BsBisTB69GhiYmLw8fGhZs2a/PLLL9m2s2LFCipUqICPjw/NmzfP1s47CQgIoHjx4pQpU4ahQ4cSGhrK6tWr8/HKCiGEEEKIvJKYNGcSkwohhCRfhRD3GB8fn2y9CdasWcORI0dYvXo1y5Ytw2g00qpVKwICAti0aRObN2/G39+f1q1b25f74osvmDVrFjNmzOCvv/4iPj6exYsX33G7PXv25KeffuKbb77h0KFDfP/99/j7+xMVFcXChQsBOHLkCBcuXODrr78GYPTo0cyePZvJkyfz77//8sYbb9C9e3c2bNgAWAPyJ598kvbt27N3715eeOEF3nnnnXy9HhaLhYULF5KQkIBOp8vXskIIIYQQomAkJs1OYlIhxH1NEUIID9WrVy+lQ4cOiqIoisViUVavXq3o9Xrlrbfesj8fHh6uZGVl2ZeZM2eOUrFiRcVisdinZWVlKT4+Psrvv/+uKIqiREREKJ999pn9eaPRqJQsWdK+LUVRlKZNmyqvv/66oiiKcuTIEQVQVq9enWM7161bpwBKQkKCfVpmZqbi6+ur/P3339nm7du3r/Lss88qiqIo7777rlKlSpVszw8dOvSWdd2sdOnSik6nU/z8/BStVqsASmhoqHLs2LHbLiOEEEIIIQpGYtKcSUwqhBBWWtelfYUQ4u4tW7YMf39/jEYjFouF5557jhEjRtifr169erar6/v27eP48eO31MbKzMzkxIkTJCUlceHCBerXr29/TqvVUq9evVtu87LZu3cvGo2Gpk2b5rndx48fJz09nUcffTTbdIPBQO3atQE4dOhQtnYANGzYME/rHzJkCL179+bChQsMGTKEV155hXLlyuW5fUIIIYQQIu8kJs2ZxKRCCAGSfBVCeLTmzZszadIkdDodkZGRaLXZv9b8/PyyPU5NTaVu3brMnTv3lnUVK1asQG3w8fHJ9zKpqakALF++nBIlSmR7Tq/XF6gdNypatCjlypWjXLlyLFiwgOrVq1OvXj2qVKly1+sWQgghhBDZSUyaM4lJhRBCar4KITycn58f5cqVo1SpUrcEuTmpU6cOx44dIywszB4I2v6CgoIICgoiIiKCbdu22ZcxmUzs2rXrtuusXr06FovFXhfrZrZeDmaz2T6tSpUq6PV6zpw5c0s7oqKiAKhcuTLbt2/Ptq6tW7fmuo83i4qKomvXrrz77rv5XlYIIYQQQuROYtLcSUwqhLhfSfJVCHFf6datG0WLFqVDhw5s2rSJ2NhY1q9fz2uvvca5c+cAeP311xkzZgxLlizh8OHDvPLKKyQmJt52ndHR0fTq1Yvnn3+eJUuW2Nf5888/A1C6dGlUKhXLli3jypUrpKamEhAQwFtvvcUbb7zBDz/8wIkTJ9i9ezfffvstP/zwAwAvvfQSx44dY8iQIRw5coR58+Yxa9asAu3366+/zm+//cbOnTsLtLwQQgghhCg8EpNKTCqEuH9I8lUIcV/x9fVl48aNlCpViieffJLKlSvTt29fMjMzCQwMBODNN9+kR48e9OrVi4YNGxIQEECnTp3uuN5Jkybx1FNP8corr1CpUiX69etHWloaACVKlGDkyJG88847hIeHM3DgQAA+/vhjPvzwQ0aPHk3lypVp3bo1y5cvJyYmBoBSpUqxcOFClixZQs2aNZk8eTKffvppgfa7SpUqPPbYYwwbNqxAywshhBBCiMIjManEpEKI+4dKuV21biGEEEIIIYQQQgghhBAFJj1fhRBCCCGEEEIIIYQQwgEk+SqEEEIIIYQQQgghhBAOIMlXIYQQQgghhBBCCCGEcABJvgohhBBCCCGEEEIIIYQDSPJVCCGEEEIIIYQQQgghHECSr0IIIYQQQgghhBBCCOEAknwVQgghhBBCCCGEEEIIB5DkqxBCCCGEEEIIIYQQQjiAJF+FEEIIIYQQQgghhBDCAST5KoQQQgghhBBCCCGEEA4gyVchhBBCCCGEEEIIIYRwAEm+CiGEEEIIIYQQQgghhANI8lUIIYQQQgghhBBCCCEcQJKvQgghhBBCCCGEEEII4QCSfBVCCCGEEEIIIYQQQggHkOSrEEIIIYQQQgghhBBCOIAkX4UQQgghhBBCCCGEEMIBJPkqhBBCCCGEEEIIIYQQDiDJVyGEEEIIIYQQQgghhHAASb4KIYQQQgghhBBCCCGEA0jyVQghhBBCCCGEEEIIIRxAkq9CCCGEEEIIIYQQQgjhAJJ8FUIIIYQQQgghhBBCCAeQ5KsQQgghhBBCCCGEEEI4gCRfhRBCCCGEEEIIIYQQwgEk+SqEEEIIIYQQQgghhBAOIMlXIYQQQgghhBBCCCGEcABJvgohhBBCCCGEEEIIIYQDSPJVCCGEEEIIIYQQQgghHECSr0IIIYQQQgghhBBCCOEAknwVQgghhBBCCCGEEEIIB5DkqxBCCCGEEEIIIYQQQjiAJF+FEEIIIYQQQgghhBDCAST5KoQQQgghhBBCCCGEEA4gyVchhBBCCCGEEEIIIYRwAEm+CiGEEEIIIYQQQgghhANI8lUIIYQQQgghhBBCCCEcQJKvQgghhBBCCCGEEEII4QAuTb5u3LiR9u3bExkZiUqlYsmSJbkus379eurUqYNer6dcuXLMmjXL4e0UQgghhBD3JolHhRBCCCGEI7k0+ZqWlkbNmjWZMGFCnuaPjY2lbdu2NG/enL179zJo0CBeeOEFfv/9dwe3VAghhBBC3IskHhVCCCGEEI6kUhRFcXUjAFQqFYsXL6Zjx463nWfo0KEsX76cAwcO2Kc988wzJCYmsmrVKie0UgghhBBC3KskHhVCCCGEEIVN6+oG5MeWLVto2bJltmmtWrVi0KBBt10mKyuLrKws+2OTycShQ4eIiopCrZaSt0IIIYTwPBaLhUuXLlG7dm20Wo8K5zxeQeJRkJhUCCGEEPcWiUfzzqNenYsXLxIeHp5tWnh4OMnJyWRkZODj43PLMqNHj2bkyJHOaqIQQgghhNNs376dBx54wNXNuK8UJB4FiUmFEEIIcW+SeDR3HpV8LYh3332XwYMH2x+fPXuWatWqsXHjRqKiopzalj1nE3j1p38oFerDvBceLPT1d52ynf8SM5jwbE1qRgUX+voLIjYulR4zdhHgrWHlaw8XyjqNRiMbN26kSZMmeHl5Fco672XfrTvB/B3neOaBkgxsXtbVzQHydgx/3Xuez/84RolgH/7Xv/A/L6Lg5DPo+eQYup9NZzbx+u+vk5CRQP0S9ZnfeX72GU6uR7P6A1RZSSg6P85UfZWHe35wSxJQuC93iknF3ZPvUc8nx9Dz3XwMjWYLzb/YBMCMXnWoEB7g4hbmLstk4ZHx1jYPbV2B9jUiXNwi55LPoYdJuYT696Goz+8C4GzxVjQaulDi0TzwqORr8eLFuXTpUrZply5dIjAw8La9DPR6PXq93v44KCgIgKioKKKjox3W1pycNfqhDTxPYNEAh2w7oOhptJZUikWWJDq6aKGvvyBSvZLQBp4mMFBfaPtsNBo5ePAg0dHR8gWdBzHRJrRHMsG/qNPf87eTl2OoO2VGG5iAJsDbbdotrOQz6PnkGLoPs8XMJxs/YeSGkSg6hVqlavHj0z8SHRptncFkgDUjYct3oAei68DTMzEnq4EP8ny7+saNG/n888/ZtWsXFy5cyFbX1Gg08sEHH7BixQpOnjxJUFAQLVu2ZMyYMURGRtrXER8fz6uvvspvv/2GWq2mc+fOfP311/j7+9vn+eeffxgwYAA7duygWLFivPrqq7z99tvZ2rJgwQI+/PBDTp06Rfny5Rk7dixt2rS5i1fRuQoSj4J7xaTi7sn3qOeTY+j5bj6GaVkmtIHW8+AixUsQXTrUxS3MXVK60d7mDF3Iffd7IJ9DD3LsT1jZH9KvQtFAaP81poB6MHShlE/KA496hRo2bMiaNWuyTVu9ejUNGzZ0UYvyx2i2AKDTOuZl16pVAJjMbjGGGgCZRjMA3l4aF7fk/hXiqwMgMd3g4pbkT3KmEQCDG72fhRCiMF1Ou0zrua0ZsWEECgr96/Tn7+f/plxoOesMCadh5uPWxCtA/Zeh7x8QWibf20pLS6NmzZpMmDDhlufS09PZvXs3H374Ibt372bRokUcOXKEJ554Itt83bp1499//2X16tUsW7aMjRs30r9/f/vzycnJPPbYY5QuXZpdu3bx+eefM2LECKZMmWKf5++//+bZZ5+lb9++7Nmzh44dO9KxY8dsg1e5O0+PR4UQ4l6VZbLY/59hsNxhTveRce18GeB0fLoLWyLEbZiNsHo4zO1sTbwWrwEvboTqT7m6ZR7FpT1fU1NTOX78uP1xbGwse/fuJTQ0lFKlSvHuu+/y33//MXv2bABeeuklvvvuO95++22ef/551q5dy88//8zy5ctdtQv5YjBZk0heGsckX21JXZPFfX5oMo3WtvhI8tVlQnytVxAT0o0ubkn+JGVcS76azLnMKYQQnmfT6U10/aUrF1Iv4Ovly/ftvqd7je7XZzi0DH59BTKTwDsIOkyEyu0KvL3HH3+cxx9/PMfngoKCWL16dbZp3333HQ8++CBnzpyhVKlSHDp0iFWrVrFjxw7q1asHwLfffkubNm0YN24ckZGRzJ07F4PBwIwZM9DpdFStWpW9e/cyfvx4e5L266+/pnXr1gwZMgSAjz/+mNWrV/Pdd98xefLkAu/f3bjf4lEhhLhXGW5IvmYaPeMcIlvy9WqaC1siRHYWxcLf+3+m2Kp3qJieYJ34QD947BPw8nZt4zyQS3u+7ty5k9q1a1O7dm0ABg8eTO3atRk2bBgAFy5c4MyZM/b5Y2JiWL58OatXr6ZmzZp88cUXTJs2jVatWrmk/flluNbz1Uujcsj6bT1fjW7UU9D2Y6KX5KvLBF/r+ZrgYT1f7clXs/tcTBBCiLtlUSyM/WsszX9ozoXUC1QpVoUd/XZcT7yasmDlUPhfN2vitUQ9eHHTbROvKSkpJCcn2/+ysrIKpZ1JSUmoVCqCg4MB2LJlC8HBwfbEK0DLli1Rq9Vs27bNPk+TJk3Q6XT2eVq1asWRI0dISEiwz9OyZcts22rVqhVbtmwplHYXxP0WjwohxL0q64ZOGxkeknzNzJZ8TUdR3OdcXtyfLqZeZMxfY3jxi1JUXtSPiukJZGn18PQP0HacJF4LyKU9X5s1a3bHL5dZs2bluMyePXsc2CrHMZpsZQcck4jUXutRa3SjZJW97ICDSi0UJkVRMJlMmM2e8UOdV0E6hRIBGrxVZjIzM13dHMBa20er1ZKZmXnb11tjMVIiQINarXKbdgurvBw/UXg0Gg1arRaVyjEX7oTzXE2/Sq8lvVh+zNpDskeNHkxqOwk/nZ91hviTsKAPXNhrfdzoVXhkOGhuXwOtSpUq2R4PHz6cESNG3FU7MzMzGTp0KM8++yyBgYEAXLx4kbCwsGzzabVaQkNDuXjxon2emJiYbPPYBmC4ePEiISEhXLx48ZZBGcLDw+3rcIX7LR4V7u1ejUfdkcQznu/mY5iRkUmJAOu5tsmY5RHnEOkZGfY2g8KlhBR75xl3IzHpvctsMbP65Gqm7JrCqiO/8bFFw1T0gJrTvqFkdppMxfJykflueNSAW57OXvPVQT1fbT1qpeZr/hkMBi5cuEB6+r1XZ8diURjRPAwVcPJkLO7wW6koCsWLF+fs2bO3/fHuXEFH+zLWE313abewysvxE4XL19eXiIiIbD0KhWfZdm4bXX7pwpmkM+g1er5r8x19a/e9/hn6dzEsfQ2yksEnBDp9DxVyD3IPHjxIiRIl7I9vHNCpIIxGI126dEFRFCZNmnRX6xJC5M+9HI+6I4lnPN/Nx9BgsjCiufX8IVibSmxsrItbmDuN0WxvM8Cl/86S4MYdlyQmvbecSz7HzD0zmbZnGmeSzhCtqFiHL/Wx5m+2hj3NRK9eDNJXc3FLPZ8kX53oetkBRw245YY9X03uX/PVYrEQGxuLRqMhMjISnU53TwVgFkXBfCkFgFLF/O09pF3JYrGQmpqKv7//7UdGvJJq/8xEhwWgVt87x8TT5en4iUKhKAoGg4ErV64QGxtL+fLl5TX3MIqi8O32b3nrj7cwWoyUCy3HgqcXUKt4LesMxkz4/T3YOd36OKoBPDUdgkrmaf0BAQH23ql3y5Z4PX36NGvXrs223uLFi3P58uVs85tMJuLj4ylevLh9nkuXLmWbx/Y4t3lszwtxv7rX41F3JPGM57v5GKYbTHBt0KpiAXpC/e7ugqQzpGYaUSVm2B8XD/ImyMf9EpsSk947TBYTK4+tZMruKaw4uhK1JRydpRx91DX4WrWDADJIUnx5y/gSq8/UA5JpeiaROqVCXN10jybJVycy2MsOOOZLypbUNVncqOerwdbz1X2/mA0GAxaLhaioKHx9fV3dHIfQeBmwKApeOr1b1N+1WCwYDAa8vb1v+6OtaAyoVNc+M3q9WySNhVVejp8oPD4+Pnh5eXH69Gn76y48Q1JmEn2X9mXhoYUAPFXlKaY/MZ1A/bWkZtxxWNAbLu0H4EL1V9gW/SLRyf7UCnJuW22J12PHjrFu3TqKFCmS7fmGDRuSmJjIrl27qFu3LgBr167FYrFQv359+zzvv/8+RqMRLy9rqYTVq1dTsWJFQkJC7POsWbOGQYMG2de9evVqGjZs6IS9FMJ93Q/xqLuReMbz3XwMTRhRaU0AaLz0HhEzZVrUqLQ3lL3Q6Ny23RKTFi5FUbiQlEkRfx16B5WmvNGpxFN8t2U28/fsJi29CHpLI0pYuuONnne18+ij+h2A3ZZyDDa/TlBkGZ4rEUT1EkE8VLaow9t3r5PkqxPZBsJyVM/X62UH3Kjnq4eUHQDu6aBLq1ZhMCuY3SgxfyeKkr2tntFqIRznXv5+ulftubCHpxc8zYmEE3ipvRjdfDyPl+nB1uPpnImPI/j4Etqd+QxvJYOrSiBvGF9m446asONfnn8ohlpRwYXantTUVI4fP25/HBsby969ewkNDSUiIoKnnnqK3bt3s2zZMsxms70Ga2hoKDqdjsqVK9O6dWv69evH5MmTMRqNDBw4kGeeeYbIyEgAnnvuOUaOHEnfvn0ZOnQoBw4c4Ouvv+bLL7+0b/f111+nadOmfPHFF7Rt25b58+ezc+dOpkyZUqj7K4Snku97IQruxnMGi4cMXHXz6Zmtw5a7ku+ownE2Pp13F+3nr+Nx+Ok0NC5fjBaVw2heMYxiAYXXY9toNjJr129M+XsHZy+HoLfURktdbNf4S6suMkE3mmoqa4mOQ2X6oG/xAasjQh2Wt7pfSfLViRzd89XWM9DgTjVfTZ6TfL2XadQqMLtXr+g7sSig3BA+eUjsJIQQKIrC1N1TeX3Fe2gND1Ja9QqBVOLbZQrf8hfeZDFcO5untOsA2GqpzGuGgcSpQigR7EOpUF9KFyn8Xm87d+6kefPm9seDBw8GoFevXowYMYKlS5cCUKtWrWzLrVu3jmbNmgEwd+5cBg4cyCOPPIJaraZz585888039nmDgoL4448/GDBgAHXr1qVo0aIMGzaM/v372+dp1KgR8+bN44MPPuC9996jfPnyLFmyhGrVpJaYEEKIu3PjqY6nnD/YBnxUoUJBIcvNk6/i7lgsCj9uO82YlYdJv3aXcJrBzKp/L7Lq34uoVFCzZDCPVAqjReUwqkQE5rsEjaIo/H74X77duJH9Z9SozVHAw9j6KUeGmmlWvjTt1Nupf2AEGmMq+IRCp8lUzsN4A6JgJPnqRNcH3HJQz1e1O/Z8tbZFkq+upbn23vCUnq83t/NOo1ALIYS7iEtLovtPY9h9UkOYZRoqrLfeJ1+7mFTb5xJfqr8i2nwaBRUHyr2I8YFBLCgaSGSwj0N7GDRr1uyO36V5+Z4NDQ1l3rx5d5ynRo0abNq06Y7zPP300zz99NO5bk8IIYTIjxt/yzyt56teqybTZHb7nq+i4GLj0hj6yz9sPxUPwIPRoYzuXJ30LDN/HrrE2sOX2f9fEnvPJrL3bCJfrD5K8UBvWlQO45FKYTQqWxQfXc55FbNFYcuJS0zavIVtJzIwGYOA0qgBBTPFQ1N4unYFnnugGpF+XBtvYIZ14VINofN0CCqR47pF4ZDkqxNdH3DLMcXztbayA26UYMswun/N1/uBbTC23N4b69evp3nz5iQkJBAcHJyndY8YMYIlS5awd+/eu2zldbckX2/4f7NmzahVqxZfffVVoW1PiLsh78n7m9misO3kVWZu+ZfVB6+A8jC2fqtVIgLoWLsEjcoWpez5pfj88T4Y08EvDFXnqVQv08yVTRdCCLflLjHpncjvv/u58RTCjU6J78iWJNZ7WZOvJosFs0Wxd57JD3lPuiezRWHGX7GM++MIWSYLvjoN7zxeie71S9sHla5eMog3Hq3ApeRM1h2+zJrDl/nrWBwXkzOZt+0M87adQa9V81C5ojxSOYwWlcII8dWx+Xgc/9t1hPVHrmIw6gDrn4UsggL/o32NUgxq2pKwAD9rY+KOwbTecOkAoILGg6HZe6CR1KCjSUbMiZw14JbRrXq+StkBR5g8eTIBAQGYTCb7tNTUVLy8vOy3h9qsX7+e0kX9OHsqNteer40aNeLChQsEBRXuSC/NmjXLNrhKbsxKwXu+zpo1K89BuiPkdV9jY2N57rnniIyMxNvbm5IlS9KhQwcOHz7s+Ea6wPr161GpVPa/YsWK0aZNG/bv3+/qpt21RYsW8fHHH7u6GcKJFEXh4PlkPl1xiIfGrOW5adtY/W8qKD4o6qu0r63n90FNWPF6E/o3KE617e/gs3ygNfEa0xRe+gsk8SqEuAfkNyZVqVScOHEi1/W6S0x6NyQmdb4bzxlud/7gbjGprZ1eGrW9w4zBZL7TIrclMan7OXophScn/c2oFYfIMll4uFxRfh/UhJ4No+2J1xuFB3rzzIOlmNqzHnuGPcqsPg/Qs2FpSgT7kGWysPbwZd5ffICGo9dSbcRK+v6wkz8OpGAw6jCTgsV7C81rHWX1m7XZ/96rfNquw/XE6z8/w/dNrYlX36LQfSE8MkwSr04ir7ITGe09Xx2bfDW5Uc3XLFvZAQclnO9XzZs3JzU1lZ07d9KgQQMANm3aRPHixdm2bRuZmZn20SfXrVtHiagooqJjMFvunJjX6XQUL17c4e3Pzc1JYk+5cp1XRqORRx99lIoVK7Jo0SIiIiI4d+4cK1euJDEx0dXNw2AwoNPpHLLuI0eOEBgYyPnz5xkyZAht27bl+PHjDtsekG3kdUcIDQ112LqFezmfmMGve8+zZM9/HLmUYp9uJpV0zV9Ujkrhl+5jKe4fbn3i0kFY0AvijoJKbe1Z0HgwqOWCpBDi3pDfmLRUqVKULVs21/W6S0x6r7vXYtLsA27deV53iUlt7VSrrJ20TAYLBpMFnwI0Q2JS92E0W/h+wwm+WXMcg9lCgF7LB+0q06VeVJ5ruHp7aWhWMYxmFcMY+YTC0UupzN2xj9/2nyI+OQiTWY1JdYVMzTZqlIZBjdvRtsJINDfHmYZ0WPk27JljfRzdGJ6cCoERhbzX4k4kI+ZEtp6vjkq+aq9dOXHHnq+3q03irhRFIc2Q5vS/vPbwrFixIhEREaxfv94+bf369XTo0IGYmBi2bt2abfrDjZsC1quoo0ePJiYmBh8fH2rWrMkvv/ySbV6VSpUt2Jo6dSpRUVH4+vrSqVMnxo8fn+NV/Dlz5hAdHU1QUBDPPPMMKSnWxETv3r3ZsGEDX3/9tf0K86lTpwA4cOAAjz/+OP7+/oSHh9OjRw/i4uLsydf09DTeH/QS4UWCiYiI4IsvvsjT63MniYmJvPDCCxQrVozAwEBatGjBvn377M+fOHGCDh06EB4ejr+/Pw888AB//vlntnVMnDiR8uXL4+3tTXh4OE899VSu+3qjf//9lxMnTjBx4kQaNGhA6dKleeihh/jkk0/sJy4A27dvp3bt2nh7e1OvXj0WL16MSqWy306XU4+KJUuWZPtBz8v+REdH8/HHH9OzZ08CAwPtg+P89ddfNG7cGB8fH6KionjttddIS0uzLzdp0qQcX4c7CQsLo3jx4tSpU4dBgwZx9uzZbD0rctvmhQsXaNu2LT4+PsTExDBv3jyio6Oz3V6lUqmYNGkSTzzxBH5+fowaNQqAX3/9lTp16uDt7U2ZMmUYOXKkvaeOoiiMGDGCUqVKodfriYyM5LXXXrOv83bHHG7tWZKQkEDPnj0JCQnB19eXxx9/nGPHjtmftx2333//ncqVK+Pv70/r1q25cOFCrq+fcA2T2cLI3/7lobFrGbvqMEcupeClUaH1PcBl3Sj+8+7BoMfC2NB/ujXxqiiw6weY2tyaeA2IgF6/QdMhkngVQuSZq+JRR8aktoH/LBaLy2NSjUbDmTNngNvHpDZpaWn07NkTf39/iUndOCYtWTSI5rUr8OaLvXKt+eouMWnDWlWY/OVYzGYzOq0aRVH45OOPJCb1YP+eT6LDd5sZ98dRDGYLj1QKY/XgpnR9oFS+B88CSDWkMmPPDHote5SPdzdmr7EH57y7Q9GPeLH1Ofa9/QFr+03iiUptb028Xj4MU1tcS7yqoOk70PNXSby6gPR8dSJbUlTvoF6gWnvZAffpJpjhoWUH0o3p+I/2d/p2U99NxU/nl6d5mzdvzrp163jnnXcAa2+Ct99+G7PZbB+dOiMjg23btjG+W08AvvtyHCsW/8zkyZMpX748GzdupHv37hQrVoymTZveso3Nmzfz0ksvMXbsWJ544gn+/PNPPvzww1vmO3HiBEuWLGHZsmUkJCTQpUsXxowZw6hRo/j66685evQo1apV46OPPgKgSJEinD9/npYtW/LCCy/w5ZdfkpGRwdChQ+nSpQv/+3UlAF9+MoxdWzfz04KFRJeM5L333mP37t23jMadH08//TQ+Pj6sXLmSoKAgvv/+ex555BGOHj1KaGgoqamptGnThlGjRqHX65k9ezbt27fnyJEjlCpVip07d/Laa68xZ84cGjVqRHx8vH1wmZz2tVixYre0oVixYqjVan755RcGDRqERnPr5yM1NZV27drx6KOP8uOPPxIbG8vrr7+e7/3NbX9sxo0bx7Bhwxg+fDhgPaatW7fmk08+YcaMGVy5coWBAwcycOBApk+fzp49e3j99ddzfB3yIikpifnz5wPYexjcaZszZ84EoGfPnsTFxbF+/Xq8vLwYPHgwly9fvmX9I0aMYMyYMXz11VdotVo2bdpEz549+eabb2jcuDEnTpywB/TDhw9n4cKFfPnll8yfP5+qVaty8eJF+wnQnY55Tnr37s2xY8dYunQpgYGBDB06lDZt2nDw4EF7b4f09HTGjRvHnDlzUKvVdO/enbfeeou5c+fm+TUUzpGUYWTgvN1sOmY9Ca8fE0rJ8AtMOziAZONFwgLD+O3JlTxS5hHrAlkpsOwN2L/A+rhcS+j0PfgVddEeCCE8laviUXBcTPr8888DMHr0aH788UeXxqQWiwW9Xk9iYiItWrTIMSZdu3YtAEOGDGHDhg38+uuvhIWFSUzqpjFp+ep1OHHuEru3b8nzgFuujkm37PmXt98YiL9ey+B33ufPFUv5fsK3/O9/EpN6miyTmW/XHGfyhhOYLArBvl6MfKIqT9SMLFDSdfeF3UzZNYV5++eRYrBeRNKqtXSo2IH+dfvTskxL1Ko75Jb2zIUVb1nLXvmHW3u7lrn1+1U4iXKfOXv2rAIosbGxTt/2Kz/uUkoPXabM2uyYbY/7/bBSeugy5cMl+x2y/oLoNOEvpfTQZcrK/RcKbZ0Gg0FZsmSJYjAYCmV9GRkZysGDB5WMjAz7tNSsVIUROP0vNSs1z+2eOnWq4ufnpxiNRiU5OVnRarXK5cuXlXnz5ilNmjRRFEVR1qxZowDKv0eOKzuOX1R8fHyVv//+O9t6+vbtqzz77LOKoijKunXrFEBJSEhQFEVRunbtqrRt2zbb/N26dVOCgoLsj4cPH674+voqycnJ9mlDhgxR6tevb3/ctGlT5fXXX7c/NpvNyvvvv688+uij2dZt+3z+tfMfZcvhs4qXTqd8PmmmkpRuPdZXr15VfHx8sq3rZjNnzszWvhtt2rRJCQwMVDIzM7NNL1u2rPL999/fdp1Vq1ZVvv32W0VRFGXhwoVKYGBgtv290c37ejvfffed4uvrqwQEBCjNmzdXPvroI+XEiRP257///nulSJEi2d6XkyZNUgBlz549t93XxYsXK7l9td+4P4qiKKVLl1Y6duyYbZ6+ffsq/fv3zzZt06ZNilqtVtLS0pTZs2ff8XW4me295efnp/j5+SlY7wxTnnjiiTxtMyMjQzl06JACKDt27LA/f+zYMQVQvvzyS/s0QBk0aFC29TzyyCPKp59+mm3anDlzlIiICEVRFOWLL75QKlSokOP3Sn6O+dGjRxVA2bx5s/35uLg4xcfHR/n5558VRbEeN0A5fvy4fZ4JEyYo4eHhOa5fUXL+nrobhf09eq86eSVVaT5unVJ66DKl0gcrlaV7zygDlw+0f2c3mdlE+S/5v+sLnN+nKN/UUZThgYoyIkRRNo1XFLPZIW2LjY1VAOXs2bMOWb9wPFfGpOLu3cvxqCNj0tOnTyuZmZmKr6/rY1Kz2awkJCQoH330kfLYY49lW7ft83nkyBElJSVF0el09t9xRZGY1F1j0guJGcq+swnKvrMJypELOb8u7haTnopLVUZ9PVkJLx6hxKdmKW9++IkSU7acxKQeZvfpeKXlF+uV0kOXKaWHLlNe+XGXcjk5M/cFb5KUmaRM2jFJqfN9nWzfyeW+KaeM2TRGuZhyMfeVZKYoyqIXrfHo8EBF+eEJRUm5VIC9yp3Eo3knPV+dKMvBZQe83LDna6at5quXZ1W48PXyJfXdVJdsN6+aNWtGWloaO3bsICEhgQoVKth7C/Tp04fMzEzWr19PmTJliI4uzapNO8jISOfRRx/Nth6DwUDt2rVz3MaRI0fo1KlTtmkPPvggy5YtyzYtOjqagIAA++OIiIgcr/ze6MCBA6xfvx5//1t7dMSePIE+qAhGg4Hqtevab30LDQ2lYsWKd1zvnezbt4/U1FSKFCmSbXpGRoZ98IfU1FRGjBjB8uXLuXDhAiaTiYyMDPttaY8++iilS5emTJkytG7dmtatW9OpUyd8ffN+7AAGDBhAz549Wb9+PVu3bmXBggV8+umnLF26lEcffZRDhw5Ro0YNe500gIYNG+Z7n3PbH5t69eple7xv3z7++eefbFe9FUXBYrEQGxtLs2bNCvQ6bNq0CV9fX7Zu3cqnn37K5MmT87zNo0ePotVqqVOnjv35cuXKERIScst2ctqfzZs322/3AjCbzWRmZpKens7TTz/NV199Zd+fNm3a0L59e7Rabb6O+aFDh9BqtdSvX98+rUiRIlSsWJFDhw7Zp/n6+mareZeXz4xwHovFwh+7T/Dmgn0kZ5ooHqjnnbbFGbbuCfZe2AvAoAaDeLfxu2iNWixmM+rdM2HVe2DOgsAS8NQMKNXgzhsSQog7cFU8att2XuUnJi1VqhT//vsv6enuE5Pu27ePdevW5RiTnjhxgoyMDAwGQ7bfdolJ3TMmbdriUeo+3IwWrduhC7hzr3F3iUkVxRqTZmVlYjJk8li7DsybPlliUg+y7J/zvPbTHiwKFPXX83GHqjxePe+39SuKwrb/tjF111Tm/zufdGM6ADqNjicrP0n/Ov1pGt30zr1cbS79Cwt6Xx9voPl78PCboM5bPsZiseSr3rMllzFlxHWSfHUiW9kBncPKDli7spvcqebrtZEafTys7IBKpcrzrVauUq5cOUqWLMm6detISEiw36IVGRlJVFQUf//9N+vWraNFixZo1SrS0601ipYvX06JEiWyrUuv199VW24uHK9SqXL9IrbdwvTZZ5/d8pxZH8Q/h67XXCqsywmpqam31CWzsdWpeuutt1i9ejXjxo2jXLly+Pj48NRTT2EwGAAICAhg9+7drF+/nj/++INhw4YxYsQIduzYke8RbQMCAmjfvj3t27fnk08+oVWrVnzyySe3nIzcjlqtvqUmm9FozPY4t/2x8fPL/n5PTU3lxRdfzFZjyqZkyZJkZmayc+dONm7cmK/XISYmhuDgYCpWrMjly5fp2rUrGzduzHWbpUqV4ujRo3d8PXLbn5EjR/Lkk0/eMq+3tzdRUVEcOXKEP//8k9WrV/PKK6/w+eefs2HDhkI95jY5fWZuPpbCdb5fvZ9Ri3ei0vsRFqCjfGQGLy+eQKapLGHaarSt0JYiljJM2XCKzKQ4BjOb0DPWcilUaA0dJ4GvDHohhLg7nhCPQv5iUrD+JoN7xaTt27dn7NixtzwXERHB8ePH76pNt9umxKSFH5MuXLqCieNGM3n8WP63Yh0UD7xtm90lJj19NY0Mg5nIYG8C/X0pHlmSJeu3c+HQDtb8+afEpG7u3/NJvLVgHxYF2taI4JMO1Qjxy9toaQkZCfz4z49M3T2V/Zf326dXKlqJ/nX606NmD4r65rFslaLA7tnWgbVMmdbxBjpPh+iH8rU/iYmJjF+2B2+/gFznzUxLoXN1iXfzSpKvTmRLvnpp8l/vIy+81Laer26UfDV4Zs1XT9G8eXPWr19PQkICQ4YMsU9v0qQJK1euZPv27bz88sto1CrKlq+ITq/n1KnTOdbSyknFihXZsWNHtmk3P84LnU6H2WzONq1mzZosX76c6OhotNrsX0Wn4tKIKh2D1suL/Xt28UA1a8+ChIQEjh49muf236xOnTpcvHgRrVZLdHR0jvNs3ryZ3r1723tXpKam3jJAgVarpWXLlrRs2ZLhw4cTHBzM2rVrefLJJ3Pc17xQqVRUqlSJv//+G4DKlSszZ86cbKME3zhoBVjrdKWkpJCWlmYP7GwDH+Rnf3JSp04dDh48SLly5W55zmKxkJmZecfXIS8GDBjA6NGjWbx4MZ06dbrjNsH6fjSZTOzZs4e6desCcPz4cRISEvK0P0eOHLntugF8fHzsJx4DBgygUqVK7N+/nzp16uR5XytXrozJZGLbtm00atQIgKtXr3LkyBGqVKmSp9dFuI7JbOGjZQeZufYQKr0flaMjUHv/y4r/NoMXlCpSlqeqPEWQPsi6QMoFOL4MzCvAzwtajoSGA6AAdb2EEMKT5TUmBahSpQp6vZ4zZ864RUxap04dFi1alGNMClC2bFm8vLzYtm2bvTapxKTuGZNWqtuIXgPfpHHVaLb+tYEGlXvkaZ9dGZMqgSlkGMxEF/FDp9WgUanw9vGh1eNt6fDEExKTurH4NAMvztlFptFCkwrF+OaZ2mjUd44BFUXhrzN/MXX3VBYcXECmKRMAb603Xap2oV+dfjwU9VD+asRmpcBvg+DAtUEL73K8AW+/APwCgwu0rLg9Sb46kcHk6AG3rB9Qo8V9rlRlmmxlByT56gjNmzdnwIABGI3GbMFf06ZNGThwIAaDgebNm6NWqfD3D6RX/4G8+eZgQOHhhx8mKSmJzZs3ExgYSK9evW5Z/6uvvkqTJk0YP3487du3Z+3ataxcuTLfBcOjo6PZtm0bp06dwt/fn+DgYF544QXmzJnDs88+y9tvv01oaCjHjx9n/vz5vPvpV/j6+dOpa3e+HDWMslHFKV+6JO+//z7qPNwyYTabbwn49Ho9LVu2pGHDhnTs2JHPPvuMChUqcP78eZYvX06nTp2oV68e5cuXZ9GiRbRv3x6VSsWHH36YrcfEsmXLOHnyJE2aNCEkJIQVK1ZgsVjst57dvK+hoaG3tHnv3r0MHz6cHj16UKVKFXQ6HRs2bGDGjBkMHToUgOeee47333+ffv368e6773Lq1CnGjRuXbT3169fH19eX9957j9dee41t27Yxa9asbPPktj+3M3ToUBo0aMDAgQN54YUX8PPz4+DBg6xevZpvvvmGVatWcenSJZo2bZrj65AXvr6+9OvXj+HDh9OxY8c7bvO7776jUqVKtGzZkv79+zNp0iS8vLx488038fHxyfU9OWzYMNq1a0epUqV46qmnUKvV7Nu3jwMHDvDJJ58wa9YszGaz/TX98ccf8fHxoXTp0rke85tf7w4dOtCvXz++//57AgICeOeddyhRogQdOnTI82sjnC8p3cjAn64PrFUrypdY40rOXT0LQIMSDWhZtiUalQZQ4NwuOLEWMjMgtAT0ngMl691hC0IIce/Ka0wK1l6Wb731Fm+88QYWi8VlMamvry9arZZXXnmFadOm5RiTTps2DX9/f/r27cuQIUMoUqQIYWFhEpO6aUyaofJm+fLlWCwWSpcpn+u6bVwZk565msE/+/dx9exxPhszmmW//ESG0UjrZg8TFhokMambMpktDJy3m3MJGZQu4su3uSRe49LjmL1vNlN3T+Vw3PU7PKuHVad/3f50q96NEJ9by1bk6sI+a5mB+JOg0sAjw6DRa3kuMyCcR46IE13v+eqo5Kt1vW5VdsBo6/kqbzVHaN68ORkZGZQrV47w8HD79KZNm5KSkkLFihWJiIhApVKhUasYMOR93nn3fUaPHk3lypVp3bo1y5cvJyYmJsf1P/TQQ0yePJnx48dTs2ZNVq1axRtvvJGt5lNevPXWW2g0GqpUqUKxYsU4c+YMERERbNq0CbPZzGOPPUb16tUZNGgQwcHBKFh/uIYM+4TaDzake5fOtGzZkocffth+dflOUlNTqV27drY/W6C3YsUKmjRpQp8+fahQoQLPPPMMp0+ftr9+48ePJyQkhEaNGtG+fXtatWqVrZ5TcHAwixYtokWLFlSuXJnJkyfz008/UbVq1dvu681KlixJdHQ0I0eOpH79+tSpU4evv/6akSNH8v777wPg7+/Pb7/9xv79+6lduzbvv//+LbfDhYaG8uOPP7JixQqqV6/OTz/9xIgRI7LNk9v+3E6NGjXYsGEDR48epXHjxtSuXZthw4YRGRkJQFBQEIsXL77t65BXAwcO5NChQyxYsCDXbQLMnj2b8PBwmjRpQqdOnejXrx8BAQG5vidbtWrFsmXL+OOPP3jggQdo0KABX375JaVLlwasx3Xq1Kk89NBD1KhRgz///JPffvuNIkWK5HrMbzZz5kzq1q1Lu3btaNiwIYqisGLFiltu6xLu4+SVVDpN3MymY3H4eGl4vqmGHVcWcC75LHqNni5Vu9CqXCtr4tWUAQcWw/E/QbFAaFnos1wSr0KI+1peY1Kbjz/+mA8//NClMWl4eDjnzp0jMjKSzZs35xiT2pKVn3/+OY0bN6Z9+/YSk7pxTNqiYR0W/DiTMd9No2zFSljycfu8q2LSLu0e4cdpkyhVyhqThoQGs2jebB57pJnbxaTJGUYS0gy5z3gfGL3yMH+fuIqvTsOUHvUI8r31NbUoFtbGruWZX56hxPgSvPnHmxyOO4yflx99a/dla9+t7HtpHwMfHJj/xKuiwPapMO1Ra+I1sCT0WQkPDwK1GovFQnx8fJ7/pHar46mU+6ygx7lz54iKiiI2Nva2t3g4yuNfb+LQhWRmP/8gTSoUK/T1/2/HGYYu3M8jlcKY3vuBQl9/fimKQtn3VmBRYPt7jxAWmL/g6HaMRiMrVqygTZs2hZLMyMzMJDY2lpiYmHwHcJ7k6MUUMk1myhT1w9+74K9bv379OHz4MJs2bSrwOiwWC8nJyQQGBubYa+DQhWSMZgveXhoyjWYigrwpFnDvHpu8OnXqFDExMezZs4datWq5rB25HT9nsn2n//nnnzzyyCMubYsjFfb3VGF/j3qyzcfjePnHXSRnmogI8qZulR1M+PtdAkydiSxWmi5VnibE51o9q+TzcPBXyEyyDmJQtgVpgWV5pXl5QkOdW/PK9n1w9uxZSpYs6dRti8LhyphU3D2JR13vbmNSd4pnPI27xqSn4tJIzrxea7ZqZCAaJx3bgsakB88nY7JYKB8WgI9Ow4WkDK6kZFHEX0+JYB8Htjh/TGYLhy6mYDFmQcoVKpYve9/GpIv3nOON/+0DYHL3OrSuln1wrYupF5m1dxbTdk/jRMIJ+/S6EXXpV6cfz1Z/lkD97esR5yozCZa+ao1JASo8Dh0nZhtvID4+Pl+1Wwe3q01oaCjx8fFMXHc8T2UH0pITaVvGizp16kg8mgdSdsCJDNcGn3LYgFu2mq9uUnbAYLZga4peyg64nO02CFM+3x/jxo3j0Ucfxc/Pj5UrV/LDDz8wceJERzTRznytjdprbXaTt7RwA2vXriU1NZXq1atz4cIF3n77baKjo2nSpImrmyY80Jwtpxjx20HMFoVqJfxI9h3HhL3LAagdXot2NZ9Eq9YCCpzdASfXW3u7+gRDlQ7WwQySE124B0IIcf9wRUwqPMvNPV0tCjjqLLSwYlJbXzjbHeu2EoW2koXuIjHDaG+r7e7W+9GB/5J4Z6F1cKyBzcvZE69mi5nVJ1czdfdUlh5ZisliAiBAF0C36t3oV7cfdSJy7+mdq/92wy99IOEUqLXw6EfQ4JUcxxuQ2q3uRZKvTmQ0W7+sHFd24FrNVzf5os40Xm+HlB1wPVvy1ZzPTOb27dv57LPPSElJoUyZMnzzzTe88MILjmgiYA2abIGTrZTG/dU/X9yJ0Wjkvffe4+TJkwQEBNCoUSPmzp3rMVfKhXuwDaw1e8tpABqW17A+oQcX48/h5+XH+PbjuXypljXxasyAw8vh6rXRrotVgoqtQSs904QQwpmcHZMKz3PzKUN+yg7kV2HEpIqi2DuZqK+dq+k07pd8VRSF+BvKDWSa7s/ka1xqFv1n7yTLZKFFpTDeeLQC/yX/x4w9M5i+Zzqnk07b521QsgH96vSja9Wu+On87n7jigLbJsMfH4LFCMGl4KlZUDL38ifCPUjy1YlsX6A6ByVfbUldk5vU68i6dkVMpXLcPou80xaw5+vPP//siObc1o3JYVublVtCqftTdHQ091mlmFu0atWKVq1auboZwoPFpWYxaP5e/joeh0oFD1S4wM9nXsSCharFqvJLl18IU4cx8dJxSDoHB5dCVjKoNdbRYyNrAfkb4EUIIcTdc3ZMKm7PXWPSm5vkyCYWRkyqcP08xxZZ6LTWvroGkwVFUfI9qJwjZBjNZBrNqFQqFMBgUrialkWJ+6hEitFsYcDc3ZxPyiS6iC+t6lyk0/86sPzYciyKNf8S7B1Mzxo9eaHOC1QPr154G89IgF8HwuFl1seV2kGHCdY7sYTHkOSrE9kG3HJc2YFrPV/N7vFDaOv56uOlcYsfjfudRlOwnq/OZmufRq2y3z3hhrGdEMIDbTh6hTd/3kdcahY+XmqKRi5jwRnrLas9a/ZkYpuJ+On8iI+Lg3M74Mpu6xeQTwhU7Qj+4XfegBBCCCFc5uaEsCN7vhaGG9tr6/nqpVFZk5yKgtFssSdjXck2yFaQtxfpivV2+u2x8XQqEuTKZjnVqOWH2BYbj5fGzHFlCM8s3mV/rknpJvSr04/OlTvj41XIdXrP7YQFfSDpDGh08NgoeLBfjmUGhHuT5KsTGa4lX700jvmgeGndq+drxrWer95S79UtaAtYdsDZbky+qq/9qLjjlXUhhOfIMpn5bNURpv8VC0DJUA1nVCM4fHkb3lpvJrSZQJ9afawXCtPirLW0TgeCjx7Cq0CFVqDRu3gvhBBCCHEnN5/muPlpj719Kq73fFWpVOg0arJMZrJMrk++WiwKiRnWQcxC/bxQKdb/bzsZT6d6Ma5smlMYzUY+XLGc+X9by0n8p/mUjIxdFPUtSq+avXihzgtUKlqp8DdsscDWCfDnCLCYICQGnp4JkbULf1vCKST56kS2sgOOqvnqdW3ALZPb9Hy9lnx1UE9fkT+2kT7zW3bA2ezJV5XKHoRI7lUIUVDHL6fw6k97OXQhGYCaMQmsuPQiJiWd8qHl+aXLL9QIr2Gd+dRfsPAFuHwe1B2h4uMQUQMpMyCEEEK4v5tLlbl7z1db+1QqVbY7RfVaa/LVHeq+JmUaMVsUdBo1fnotRoM1GbzrdAIGk8Vhd/W62on4E0zbPY1ZO9ahSxqKCkjUzqNROX/61ZlPx0od0WsddGE+PR4WvwTHfrc+rtoJ2n8D3oGO2Z5wCkm+OpGt7IDeUWUHrvWotfWwdbVM6fnqVgo64JazmZUbyw5Y2+we72ghhCdRFIUft57io4U7yDRaCPbREhK+mqUnpwDQoVIHvmr9FYFegcTHXYEtEwje+RVqlQKhZSHyWShe1sV7IYQQQoi8suVa1SoVFkVBcfPzHssN7b2RLaHpDslXW8mBED8dKpUKby8NGjWkG0zsPBVPo3JFXdzCwpNlymLJ4SVM3T2VNbFrUCvBRGR+hQodJYpdZXXvkZQvUs6xjTi9BRb2heT/rHddPT4G6vaRMgP3AEm+OonZcn0kQ4f1fL2WfHWbnq/Xfiwk+eoerpcdcP2P+J3kXPPVPd7TQgjPEJ9mYOjCf1i16ziWrDSKFw3gsnktp89dJVj1NC2iH6F2YC1+/PsyGGPh6CoyL55kcICF0AbdoOF7sPmCq3dDCCGEEPlguaETh8WsuH0HDltyWH1TXs2WfM1ycfI1y2QmNcta4zXEVwdYe+l6XyuFsPbw5Xsi+Xok7ghTd0/lh30/EJceB4BK8aKC+jMyKEqZYn78OuAxAry9HNcIiwU2fwlrR4FihiLl4OlZULwQB+4SLiXJVye58aqVl8MG3LKVHXCPn5kMg63n6715K4KnsfV89ZiyAzLglhCiADYfj2Pwz3u5lJyFl0ZFREk1h7OWYdaYCQ0J5+kqTxEZUMI6c8IpOPIbGNLAzxfajIOm/SE+3qX7IIQQQoj8s50zaNQqjGZrvVJ3Zq/5elOvRtudsq6+ozUhzVrf1V+vzVZewNa5au2Ry3zQropL2na3MowZLDy0kCm7prDpzCb79BIBJehbuy9JV1qzZHc8AXotU3vWc2ziNfUKLH4RTqyxPq7eBdqNB32A47YpnE6yYk5y4xenzmE9X63rNbrJj0yWScoOuJMbyw44oyepSqViyZIl+V4uW/L1Wp3FO7V21qxZBAcH2x+PGDGCWrVq2R/37t2bjh075rsddyM6OpqvvvrKqdsU4n5nMFkYvfIQ3adv41JyFjFFfahQ7g/2JyzHrJipWKQiL9btb028KhY4tQn2zb+WeC0GNZ6F6k+5ejeEEEIUsoLGpPklManr3Zh8BU8YcOs2PV8118sOuOoOQEVRSEi3lhwI9dNle07vpUajVnHyShqnr6a5onkFtv/Sfl5b+RqR4yPpsbgHm85sQqPS8ETFJ1j27DJODzpNFf++LNkdj0oFXz1Ti7LF/B3XoFN/weSHrYlXrQ888R08OUUSr/cgSb46ifGG5KutPEBhu152wD16vkrNV+fYsmULGo2Gtm3b3nE+7Q2/6rYEp6sDsoGgt7QAAQAASURBVIsXL/Lqq69SpkwZ9Ho9UVFR9HqmM9v+2oBGpbIHIvkplv/WW2+xZs0aB7U4u5uDbJsdO3bQv39/p7RBCAEnr6TSedLffL/hJIoCrWv4c173Or+fnoEaFY+VeYxnqnXFW+sDWSnWpOupzdaFI2pCnZ7gG+ranRBCCA+X15g0J+4Yk7Zv3/6uYkqJSZ1LURT7gFuaaz1J3b10mWJPvmbPD3hp1aiw1q111V2LqVkmjGYLGrWKQJ/svT7VKhXVIq2DP609fNkVzcuXNEMaM/fMpOH0htSYXINvt39LYmYipYNK83Hzjzk96DS/PvMrbSu0Zd+5ZD5c8i8Ab7SswCOVwx3TKIsZ1o+FH9pD6kUoWhH6rYU6PaS+6z1Kyg44ia3sgE6jvuW2gsKitfV8dZear0brPvtI8tWhpk+fzquvvsr06dM5f/48kZGROc6nUqnQqFWYLdYfca2LD8uZM2d4/PHHCQ4O5vPPP6d69eoYjUbmL/qNTz8YwpPtWts/K/mJm/z9/fH3v7urkwaDAZ1Ol/uMt1GsWLG72r4QIm8URWHBznMMX/ovGUYzwb5etK5zlW/2PU2GKYOIgAg6lniW8iWrWReIPwmHloExHTQ6qNAawj3zdjkhhHA3eY1J3c2pU6do3LjxLTHp77//zoABAzh8+HCB1isxqXPdmKP0nJ6v1n/VN3V9VatUeGlVGEwKBpPFYWPG3Em8baAtX90tyWGA+mWKsOJQPGsPX6bPQzHObl6e7L6wm6m7pjLvwDySs5IB0Kq1dKjYgf51+9OyTEvUquuv7eXkTF6aswuD2UKrquEMbO6gwbVSLsGifhC7wfq4Vjdo8zno/ByzPeEWpOerk9h6vjqq1ytc79lodJOerxnXer7qPbDmq6IopBtMTv/L79XZ1NRU/ve///Hyyy/Ttm1bZs2adcs8v/32Gw888ADe3t48XK0Mg17ojtmi0KxZM06fPs0bb7yBSqWyJzpvvkUK4KuvviI6Otr+eMeOHTz66KMULVqUoKAgmjZtyu7du/PV9jfffBOVSsX27dvp3LkzFSpUoGrVqvR+aSBzfl19rewAzJ4ygbZN6+Pn50dUVBSvvPIKqampt11vTu0HGDlyJMWKFSMwMJCXXnoJg8Fgf65Zs2YMHDiQQYMGUbRoUVq1agXA+PHjqV69eo7bXr9+PX369CEpKcn++o0YMQK4tffGmTNn6NChA/7+/gQGBtKlSxcuXbp0S5vnzJlDdHQ0QUFBPPPMM6SkpOTrNRXifpKUbmTAvN28vfAfMoxm6scEU7XSr4zd9RwZpgxalW3F+l7riQwsaS0zcHI9/POzNfHqHwZ1e0viVQjh1lwVjzojJi1atCidOnUCcHlMOmDAgBxj0sGDB7N161b7fHeKC3MiMalz3fievZ58de/sq619OWUIbKUHXDHolslsITkz+0BbN6sfUwSAbSfjSbs2KJc7SM5K5vud31NvSj3qTqnL5F2TSc5KplxoOca2HMu5N87xS5dfeKzsY9kSr5lGMy/9uIvLKVmUD/Pniy61bkmKF4qT661lBmI3gJcvdJwMHSdK4vU+ID1fncSefHXQYFtwvearuwyo5MllBzKMZqoM+93p2z34USt8dXn/WP78889UqlSJihUr0r17dwYNGsS7775rD1qXL19Op06deP/995k9ezbHLybw5++rMFsUFi1aRM2aNenfvz/9+vXLVztTUlLo1asX3377LYqi8MUXX9CmTRuOHTtGQEDu9Wni4+NZs2YNn3zyCX5+2X9oLBaFwKAge9CkVqt5/5PPaFK3KidPnuSVV17h7bffZuLEiXlu75o1a/D29mb9+vWcOnWKPn36UKRIEUaNGmWf54cffuDll19m8+bN9mlqtZpvvvmGmJiYW7bdqFEjvvrqK4YNG8aRI0cAcuzdYLFY7EHuhg0bMJlMDBgwgK5du7J+/Xr7fCdOnGDJkiUsW7aMhIQEunTpwpgxY7K1UQhhdT4xg27TthEbl4ZWraLnQ6EsOP0iBw79g1qlZmSzkbzX+D0SExLBcBb2LoOkc9aFI2tDuUdALSGQEMK9uSoeBcfHpAaDgRUrVgC4NCZNSEjg999/Z9SoUbfEpEC2W/nvFBfmlcSkjmM7A1ahsp9HuHvZgdv1fAXroFupWdkH7naWhHQjiqLg46XBR5fzuXzpIr6UDPHhXEIGm4/H8VjV4k5u5XWKorD9v+1M3T2V+Qfmk2a01qHVaXR0rtyZfnX60TS6abZk640sFoW3Fuxj95lEAry1TOlZD399IceJZhNsGAsbPwcUCKsKT8+CYhUKdzvCbcmZh5Nk3VB2wFFsvWptAyo5qrxBXtnKDni7+v72e9j06dPp3r07AK1btyYpKYkNGzbQrFkzAEaNGsUzzzzDyJEjAfAulkbp8lUwWRRCQ0PRaDQEBARQvHj+fixbtGiR7fGUKVMIDg5mw4YNtGvXLtfljx8/jqIoVKxY8Zbn7ANuqVQoQPcXXkav1RBdPIDo6Gg++eQTXnrppXwFujqdjhkzZuDr60vVqlX56KOPGDJkCB9//DFqtfUzWb58eT777LNsyw0aNMj+/5u3rdPpCAoKQqVS3fH1W7NmDfv37yc2NpaoqCgAZs+eTdWqVdmxYwcPPPAAYA2IZ82aZT9R6NGjB2vWrHH7QFcIZzsbn85z07ZyNj6DEsE+dGpwlZFbupJqSCXcL5x5nefRIubad9TxtbB3hTXa0eqtZQbCKru0/UIIcS/Kb0wKULNmTQCXxqQnT55EURQqVaqU67x3igvzSmJSx7H3IlVdL5npJn2Sbku5zYBbALpr59CGa4NYO8udBtq6kUqlokWlMGZvOc26I5ddknxNyEhg7v65TNk1hf2X99unVypaiX51+tGzZk+K+hbNdT2f/3GEZf9cQKtW8X33usQULeReqMkXYGFfOH3tgkqdXvD4WPDyKdztCLcmyVcnsdVhdWS9Fu0N6zaaFXRaVydfrT8UPjrPKzvg46Xh4EetXLLdvDpy5Ajbt29n8eLFAGi1Wrp27cr06dPtge7evXuz9SCwXQU2W+7uCuqlS5f44IMPWL9+PZcvX8ZsNpOens6ZM2fytPydrkLbk69qFWZFYeum9cyc+CVnTh4nOTkZk8lEZmYm6enp+Pr65ml7NWvWzDZvw4YNSU1N5ezZs5QuXRqAunXr3rLcn3/+yejRozl8+HCBt33o0CGioqLsQS5AlSpVCA4O5tChQ/ZANzo6OlsPjYiICC5fdv8C9kI405mr6Tw7dSv/JWZQKtSHcmWXM2TDeACalm7KT51/IiIgAsxG+HMErP0WjO0hpDRU6QA+Ia7dASGEyAdXxaO2bedVQWLSwuLImPRmhREXSkzqOLZDqVJdH8DKU8oO5FRTVXftjtksJ5cUzDCayTSaUatUBPl63XHe5rbk6+ErTuv8pSgKf535i6m7p7Lg4AIyTZkAeGu96VK1C/3q9OOhqIfy3JZ5284waf0JAMZ0rkGjcrkna/Pl2J+wuD+kXwWdP7T/Gqo/VbjbEB5Bkq9OYh9wy6FlB65/wRjNFoduKy/sZQc8sOerSqXK161WrjB9+nRMJlO2wQwURUGv1/Pdd98RFBSEj0/2q2m2usB3Kk2hVqtvCUSNRmO2x7169eLq1at8/fXXlC5dGr1eT8OGDbPVrLqT8uXLo1Kp7LdG3dh+s3I9+Rp7IpZX+zxD1559+fLzsYSGhvLXX3/Rt29fDAZDnoPNvLj5VrNTp07Rrl07Xn75ZUaNGuXQbQN4eWUPblQqFZa7TJILcS+JjUvjualbuZCUSVSojhT/j5l5YD0A7z38HiObj0Sr1kLCafjlefhvp3XByFpQva2UGRBCeBxPiEehYDFpXjgjJi1btiwqlSrXQbWcGRdKTFowyg2JTFtPUjfPvdp75uaUJ9RfO5d3dtkB20BbgT5eaNV3zic0LFMEby81F5MzOXghmaqRQQ5rV1x6HLP3zWbq7qkcjrv+ea0RXoN+dfrRrXo3QvJ5kX39kct8+OsBAF5/pDxP1S1ZeA02G2HdKPjrS+vj4tXh6R+gSNnC24bwKJ7XJdFD2Wq+OrLswI1fjiaz639pPLnmq7szmUzMnj2bL774gr1799r/9u3bR2RkJD/99BMANWrUYM2aNfblrvd8tb4/dDodZnP2W1mKFSvGxYsXswW7e/fuzTbP5s2bee2112jTpg1Vq1ZFr9cTFxeX5/aHhobSokULJk6cSFpamn26rV3JSUmo1Sr27NmDxWJhyLBPaNCgARUqVOD8+fN53o7Nvn37yMjIsD/eunUr/v7+2a7832zXrl1YLBa++OKL2247p9fvZpUrV+bs2bOcPXvWPu3gwYMkJiZSpYoM9iNEXhy/nErX77dwISmT8CCFA6Z+7L2ynlCfUFY8t4JRj4yyJl4PLYPvG1sTr95B1kEMYppK4lUIIRykoDHpzVwVk4aEhPDYY48xYcKEbDGpTWJiIpC3uDAvJCZ1HMu91vP1Wt7AbFEwOan3q8WikJRuvcARmkuvV7Ce5z9U1tpTdP2RK4XfHsXC2ti1PLvwWUqML8Gbf7zJ4bjD+Hn50bd2X7a9sI29L+5l4IMD8514PXg+mQFzd2O2KDxZpwSDWpYvvIYnnYNZba8nXh94Afr+KYnX+5wkX53EYB9wy3Fd8bP1fHWDq5P2mq9e8jYrbLYC+H379qVatWrZ/jp37sz06dMBGD58OD/99BPDhw/n0KFDHD30LzMmfmVPckZHR7Nx40b+++8/e6DarFkzrly5wmeffcaJEyeYMGECK1euzLb98uXLM2fOHA4dOsS2bdvo1q1bvns0jBs3DrPZzIMPPsjChQs5duwY/x48yNwZ39Oz42OoVSrKlSuLyWhk7vTvOXnyJHPmzGHy5Mn5fr0MBgN9+/bl4MGDrFixguHDhzNw4EB7ba2clCtXDqPRyLfffnvbbUdHR5OamsqaNWuIi4sjPT39lvW0bNmS6tWr061bN3bv3s327dvp2bMnTZs2pV69evneFyHuN0cvpfDMlK1cTski0C+VnVndSTSepkHJBux9cS+Pl38cTFmw8h34XzfITIISdeHFTVCxtaubL4QQ97SCxqT79+9n7Nix9vW4Mib97rvvbolJDx06xDfffEPDhg2BvMWFeSExqePYyw6gst9y7v41X63/5lTzVa1W2UsWGpyUfE3KMGJWFHRaNX55HHCqeaUwANYeLrzSFJdSLzH2r7FU+LYCj8x+hPkH5mMwG6gbUZfJbSdz/s3zTHtiGg+WeLBApQ4uJGXw/KwdpBnMNCxThDFP1ii8kglHVsHkh+HsNtAHWnu7tv0CvLwLZ/3CY0lWzElstws4suarSqW6flu5O/R8NUnPV0eZPn06LVu2JCjo1ls7OnfuzM6dO/nnn39o1qwZCxYsYOnSpdSqVYtO7VpzYO9ue9mBjz76iFOnTlG2bFmKFSsGWK+KT5w4kQkTJlCzZk22b9/OW2+9dcv2ExISqFOnDj169OC1114jLCwsX/sQHR3Nzp07ad68OW+++SbVqlWjzeOt2f7XBoaPsdZwrFWzFm8NG8WMiV9TrVo15s6dy+jRo/P9ej3yyCOUL1+eJk2a0LVrV5544glGjBhxx2Vq1qzJ+PHjGTt27G233ahRI1566SW6du1KsWLFbhkcAayfy19//ZWQkBCaNGlCy5YtKVOmDP/73//yvR9C3G8OXUjm2SlbiUvNQqu/yL/m/lhUSQxuMJgNvTcQFRQF8bEw/THYNsm6UMOB0GeVtc6rEEIIhypoTNqiRQu2b99un9eVMWmZMmXYvXt3tpj00UcfZc2aNUyaZP1tyUtcmBcSkzqOwvXBq2zJTE/u+QrXe786q/RA/LWBtkJ8dXlORtqSr3vOJJCQlrdyHzmxKBZ+P/47nX/uTMkvS/LOmnc4kXCCAF0AL9V9iV39d7Gz/05erPcigfrAAm8nJdNIn5k7uJicSfkwfyb3qFs45RpNBvj9ffipK2QkQGRteHEjVO149+sW9wSVkp8q4/eAc+fOERUVRWxsLNHR0U7b7rJ/zjNw3h7qx4TyvxcbOmw7lT5cSabRwqa3mxMVWrj1f/Kr6/db2BYbz7fP1qZ9zcjcF8gjo9HIihUraNOmzS01iQoiMzOT2NhYYmJi8Pa+t69IpWQaiY1Lw9tLQ4XwgNwXcBCLxUJycjKBgYHZrvTf3D6T2cLBC8kAVC8R5JQi7iJ3tzt+wnEK+3uqsL9HHeHAf0n0mL6NhHQjZk0s573eJcBbw8wOM+lUuZN1pn+XwNJXISvZOphWx0lQ8XH7OuLj45m47jh+gcG5bi8tOZFXmpcjNDS0wMs506lTp4iJieHs2bOULFmINcqE07gqJhWFQ+JRzyfxjOe78RimZJk5fTUNX52WiCBvTlxJRa/VULG46855chMbl0ZKppGSIb6E+uluef5sfDoJ6QbCA70JD3Ts90KWycyRiykAVCoeeNuEZE7fVa2/2sjhiyl81bUWHWuXyNd2T8Wf4r0F7/F3xt+cTjptn96gZAP61elH16pd8dP53WENeWc0W+j7w042Hr1CUX89i19pVDg5k5vHG6j/Mjw6ErT6u193ATkrBm5bxos6depIPJoHUgTNSew1Xx08CJaXWk0mFvv2XCnTZCs7ID1f3YX2ppqv7sbWLs21JOuNuVZFybkYvRDi3vPPuUS6T9tGcqaJLNURLnkNo3ZkRRY8vYAyIWXAmAl/vA87plkXiGoAT02HIAn6hBBCiPuRrU+ZSnX9nMFzer7m/LwzB92y9VoN8PbKd86ieaUwDl9MYe3hy3lKvposJlYdX8WUXVNYfmw5FsW6f8HewfSo0YN+dfpRPbx6/nfiDhRFYdivB9h49Ao+Xhpm9K5XOInXQ8vg11esZa+8g6DDRKjc7u7XK+45knx1EmeUHQDQanIfzd5ZsuwDbsmVZHehuXZV32RRUBTF7XqS2pOvalvy9Xr7rLcSuVd7hRCFb8+ZBHpM30ZqlplM9UEu60bw0gO9GN9qPN5ab7h6Ahb0gov7rQs8/AY0fx807tmDVwghhBCOd71+qspjBty6sc050Tkp+aooCgnXBtoKycNAWzdrUSmMSetPsOHoFUxmC9rb5DxOJ55m+p7pzNgzg/9S/rNPr+JXhSGPDKFrta74eOWvZnNeTdpwgp+2n0Wlgm+erU2NksF3t0JTFqweBtuu1V8uUQ+engnBpe66reLeJMlXJzFcq8Gqc3jy1bp+t+j5ei356iM9X92GLampKAoWBTRulss0KzclX294zqKAvJOEuLftPBVP9+lbyDRCpvoAaf7jmPfEdJ6p9ox1hv2/wG+vgyEVfItApylQvqVrGy2EEEIIl7Ncq/mq4npPUjfPveba89WWfM1ycPI1JdOE0WxBq1YR6JP/5GvtqGCCfLxIyjCy52wiD0RfL8VkNBtZdnQZU3ZP4ffjv9tr8xbxKULvWr3pVb0XJ7efpE01x5XCWrrvPJ+tOgLA8HZVeLRK+N2tMP4kLOgDF/ZaHzd6FR4ZLh0BxB1J8tVJjLaerw4uO2BL7rrDgFsZRhlwy92oVdbepIqiYLZY0Kjd69jk1PPV1l53D56EEHdny4kr9JixBZNZQ6Z6H0VL/MKGrn9RsWhFMGbAyqGw+wfrzKUfgs7TILDw6okLIYQQwnPZzhVUqut3z1kU97zbz8ZiL5Vw556vJosFs0WxnyMVtoRrA20F++pu2wv3TrQaNU0rFGPpvvOsPXyZB6JDORF/gmm7pzFz70wupV2yz/tIzCP0q9OPjpU6otfqMRqNnORkoe3LzXaciuetn/cB0PfhGHo/FHN3K/x3MSx97dp4A6HQaTJUaFUILRX3Okm+OonBVvPVaWUH3KHnq63mq5QdcBcqlQqtWoXRrGCyKNxa1t21bk6+gvXqtcL1Ok5CiHvP8gPHGTj3AIriRYZ6N63rnWFS+7/w9fKFK0dgQW+4fBBQQZMh0HQoaCSEEUIIIYSVYu9FqsqWQHTncSMsuZQd0KrVaNUqTBYFg8mCj67wO86YzBaSM00AhOQw6FdetagUxtJ951m89yirLw9kTewa+3PhfuH0qdWHvnX6Ui603F23Oa9OXkml3+ydGMwWWlUN5702lQu+MmMm/P4e7JxufRzVAJ6aAUH5G2BM3L/kzMVJbD1fdVrHfvPbBlQymFyfqLKVHdBr3at35f1Oo1ZhNLvnoFuWHJKvapU1MHG/1gohCsPXG9YzfmUCKnRkaXbzSaeS9Kv3ofXJvT/B8sFgTAe/MHhyCpRt7toGCyGEEMLtWG7o+XpjB1GLoqB203EjFMudyw4A6LQaTAYTBrMZHwcUYUtIN6IoCj46TYHLBR6JO8Ka8zNReIiLiRrOZfyDSq2iVblW9KvTj/YV2uPl5Fvyr6Zm0WfWDhLTjdSMCuarrrUL3nM47ri1I8Al23gDg6+NNyDpNJF38m5xElsNVkcPuGVbv6t7vlosir02jSOu0ImCsyXo3TH5ahsoTnPD1V/rbTiK9HwV4h5jsVjoNucHthwKQ4UOtfe/LO/XgTolaoAhDVYMgb1zrTPHNIEnp0HAXdboEkIIIcQ96XrZAVW20mVueMpjZztjv1NZBJ1WTbrBMXVfFUUhIc1aciDUN3+9XjONmfxy9Bem7JrCpjObAAhXf4a3pQqdyw5j7BPtiA6OLuwm57FtZvrN3snpq+lEhfowrWe9guck/lkAywZdG2+gKDz5PZST8QZE/kny1UmynF12wMU1X2/8cZCar+7FdsXP5IaRiEXJueyA9TkXNEgI4RAXU67y+MQ5JCSUB6B42GFWvvQSIb6BcOmgtXdB3BFQqaHZu9D4TXCzGtVCCCGEcB+2gZxspxFqFZiV6+cX7sZWjxZy6fl6LX9gcEDyNcNgJtNkRq1SEeSbt56pGcYM4jPi6TqrK/vjrT1B1So1bcu3pZSmEst2g7+lfqEkXtcdvszfJ+IwWRTMFgWj2TpuielaCT3rNGs9XJNFwXTtuSupWZy8kkaQjxczez9IsQB9/jduSIdVQ2H3bOvj6Mbw5FQIjLjr/RL3J0m+OonxWhkARw+4Zev5autp6yq2kgMA3g7eZ5E/Gjfu+ZpjzddrV4Ldr7VCiIJYfWwb/WbvAGN5FMy0rp3E5C6DrRdads+GFW+DKQP8i1sH1Ypp7OomCyGEEMLN2Xu+Xuu6oVapMLvx3XM3tutOg1zptY5LvsZfG2gryMcLrfr25+xmi5mEzASupF0hLSONlKwUkrOSKR1Umr61+9Kndh9KBpbk4Plklu3exOYTcWQazXfVCWvO1tN8uORAgZfXadR836Mu5cL887/wzeMNNH3bOt6AdAQQd0GSr05iMFuTkQ4vO6C2lR1w7Y9Mpsm6v1q1Cq2D91nkT17KDowYMYJJkyZx+fJlFi9eTMeOHZ3SNts1g+zJV+u/+Qmc1q9fT/PmzUlISCA4OJhZs2YxaNAgEhMTAev+LVmyhL179xZSy3PXrFkzatWqxVdffeW0bQrhThRFYfjqacxc54VGiQFVGh91iqLXg09AVgosGwz7f7bOXLYFdJoC/sVc22ghhBAu5aqYtLBITOo8th6uqht6vlqnu6hBubixXXcaEEznoOSr2aKQlG4EIOQ2vV7TDGnEpccRnxGPWbGe36tQ4evly7T202hevjmaGxKSlSMCiAjy5kJSJltOXqV5xbACtW3BzrP2xGvb6hFEF/VFc23wMa3GOoC0Rq3GS6NCo1bhpVajsT9n/X+1EoGUDPHN/8b3zoPlb14fb6DzVCjTrED7IcSNJPnqJLaer3oH9wK1lR1wfc/Xa/VepeSAw/Tu3ZsffvgBAC8vL0qVKkXPnj1577330Gpv/9HW5JKgP3ToECNHjmTx4sU0aNCAkJCQu25rXgJLRbHeOpKaksyICZ+xZPEiTp06RUBgEGUrVmbgK6/Q7Zmn71gT6Xa6du1KmzZt7mIP8u7mINtm0aJFeHk5t9C8EO4iJSuFzrM/4vCJBmjwRq9P5Of+LahZIgIu7rf2Lrh6HFQaaPEBPDQI7tADQwghhPsoaEyaG1fFpDbJycmMHTuWhQsXcurUKYKDg6lWrRqvvPIKnTp1kpjUzdj6adiSrrbj465lB66XHFDlWvMVwGC2WAcPK8D7LidJGUbMioJOq8ZPf/1zaraYic+I50r6FdKN6fbpeo2eor5F8Vf7cy7tHDGlY7IlXsH6mjerGMZP28+w7vDlAiVfl+47z9CF/wDQu1E0w9tXKdBnLd8MabD8Ldg3z/o4pqm1zICMNyAKiSRfneT6gFuO/eLQ2ssOuPZHJsNgvTKml+SrQ7Vu3ZqZM2eSlZXFihUrGDBgAF5eXrz77ru3XeZ2ZQfMZjMqlYoTJ04A0KFDB+f80F1jUSApKZHeT7YmKz2VTz75hAceeIDzSVls2rSRYR+8S7vHH8sWPOaVj48PPj4+d9U+g8GATpe/QvQ3Cg0NvavtC+Gp9l3cx5Mzvsec3BY1UKpYGr+9/DRBPl6wYzqsehfMWRBYAjpPh9INXd1kIYQQ+VSQmPR2XB2TAiQmJvLwww+TlJRkj0m1Wi0bNmzg7bffpkWLFhKTupnrPV+vlx2A60lZd2OxJ4vv/N7WqlWoVSosioLBZCm08VQS0rMPtJVqSLX3crUo1tyFChUhPiEU9S1KgC4AlUpFZmbmHdfbopI1+br28GVGPqHk67O76sBF3vjfXiwKPPtgKeclXi8dhAW9IO7otfEG3oPGg6XMgChU0q3ESbLsyVdHlx2wDbjl4p6v18oOeHt56FtMUaxXv5z9l8/oQK/XU7x4cUqXLs3LL79My5YtWbp0KQBZWVm89dZblChRAj8/P+rXr8/69evtZQd+njeH4OBgli5dSpUqVdDr9Tz//PO0b98eALVane3Hbtq0aVSuXBlvb28qVarExIkTs7Xl3LlzPPvss4SGhuLn50e9evXYtm0bs2bNYuTIkezbt88+8uisWbNu2RezReHbsR9x/txZtm7dSq9evahSpQplypWn83O92LhlB/7+1po9c+bMoV69egQEBFC8eHGee+45Ll++fNvXadasWTkGyN9//z1RUVH4+vrSpUsXkpKS7M/17t2bjh07MmrUKCIjI6lYsWKu2z516hTNmzcHICQkBJVKRe/evQHrLV6DBg2yrz8hIYGePXsSEhKCr68vjz/+OMeOHbulzb///juVK1fG39+f1q1bc+HChdvupxDuZsrOGTz23TzMyW0BaFVdz9pBTxGkzoRf+sDywdbEa/lW8NJfkngVQogbuSoedVJMamOLeZwdk2o0GubNm5fj/rz33nucOnWKbdu22WPSChUq0K9fP/bu3SsxqRvGpNdrvlpdLzvgntlXSx4G2wJrMrmwSw9kGc2kZZlQAWZVMgevHORw3GHi0uOwKBa8td6UDCxJjfAalAkpQ6A+MM9J0IfKFUGnVXMuIYPjl1Pz3Kb1R6/w6k+7MVsUnqxTglEdqzk+8aoosOsHmNrcmngNiIBev0HTIZJ4daCNGzfSvn17IiMjUalULFmyJNvziqIwbNgwIiIi8PHxoWXLltm+kwDi4+Pp1q0bgYGBBAcH07dvX1JTs7/f/vnnHxo3boy3tzdRUVF89tlnjt61O5Ker05ivPZFqXPWgFuurvlqtCVfPfRLy5gOn0Y6f7vvnQedX4EX9/Hx4erVqwAMHDiQgwcPMn/+fCIjI1m8eDGtW7dm2649qIIisFgU0tPTGTt2LNOmTaNIkSJERETQrFkz+vTpky2gmjt3LsOGDeO7776jdu3a7Nmzh379+uHn50evXr1ITU2ladOmlChRgqVLl1K8eHF2796NxWKha9euHDhwgFWrVvHnn38CEBAQgNFozNZ2o8nMqqWLaNfpaUqUKGGfbvvR9fXzt9+6ZjQa+fjjj6lYsSKXL19m8ODB9O7dmxUrVuT5tTp+/Dg///wzv/32G8nJyfTt25dXXnmFuXPn2udZs2YNgYGBrF69+no777DtqKgoFi5cSOfOnTly5AiBgYG37d3Qu3dvjh07xtKlSwkMDGTo0KG0adOGgwcP2m8FS09PZ9y4ccyZMwe1Wk337t156623srVRCHeUZkjjhSWDWb+nAj5KE8DCO23K8FKTqnB+DyzoAwmxoNZCyxHQYICUGRBCiJu5Kh4Fp8Sk+/fvp3z58gAuiUktFkuOyR2LxcL8+fPp1q0bkZG3vv62xCtITOpOMant7Nd2TK+XHXBRg3Jha1deEox6rZpMoxlDIXSwUhSFSylp1jao0vkv5by9HaHeodbSAjr/Aic+fXVaGpQpwsajV1h7+DLlwwNyXeZIkoppP+3DaFZoWyOCzzrXQJ1bVvpuZaXAsjdg/wLr43ItodP34FfUsdsVpKWlUbNmTZ5//nmefPLJW57/7LPP+Oabb/jhhx+IiYnhww8/pFWrVhw8eBBvb28AunXrxoULF1i9ejVGo5E+ffrQv39/+wW15ORkHnvsMVq2bMnkyZPZv38/zz//PMHBwfTv39+p+2sjyVcnMTqp56ut5qure75mSc1Xp1IUhTVr1vD777/z6quvcubMGWbOnMmZM2fsQeNbb73FqlWrmDv7B7q/+g4WRcFoNDJx4kRq1qxpX5ftanzx4sXt04YPH84XX3xh/3KMiYnh4MGDfP/99/Tq1Yt58+Zx5coVduzYYb+VqVy5cvbl/f2tiVPbOi0Wyy3J18tXrpCclEjZ8hWyTbf97N444Nbzzz9v/3+ZMmX45ptveOCBB0hNTc0WEN9JZmYms2fPtid6v/32W9q2bcsXX3xhb6efnx/Tpk3LdmtXbtu27X9YWNhtb0ezBbibN2+mUaNGgPVkIioqiiVLlvD0008D1qB68uTJlC1bFrCevHz00Ud52j8hXOVw3GE6/fgaKZeeQ68UQ+9lYnqvRjxctihs+x7++ADMBggqBU/NgKgHXN1kIYQQhSQ/MenMmTP59NNPAVwSk1osFpKTk2/Zh7i4OBISEqhUqVKu+ysxqfu4uSfpvdLzFQpn0C2j2cjVjKvEpV/FbAhHhRYzyfhofSjqW5QivkXQqgsnPdSiYjF78vXFpmXvOO+OUwlMO6zGYLHwaJVwvupay/EDdl/4x3oHlm28gUc+hEavS0cAJ3n88cd5/PHHc3xOURS++uorPvjgAzp06ADA7NmzCQ8PZ8mSJTzzzDMcOnSIVatWsWPHDurVqwdYvzfbtGnDuHHjiIyMZO7cuRgMBmbMmIFOp6Nq1ars3buX8ePHS/L1Xme7SqVzdNkBe81X1yZfM4weXnbAy9d6xd8V282HZcuW4e/vj9FoxGKx8NxzzzFixAjWr1+P2WymQoXsicysrCx7IGZRQKfTUaNGjTtuIy0tjRMnTtC3b1/69etnn24ymQgKCgJg79691K5d+65qSNkuGNxc98j28MawadeuXYwYMYJ9+/aRkJCAxWJd9syZM1SpUiVP2ytVqlS2HrYNGzbEYrFw5MgRe6BbvXr1W2pqFca2Dx06hFarpX79+vZpRYoUoWLFihw6dMg+zdfX1x7kAkRERNzxVjYhXG3e/nkMXDQN/4wBaPEmIljFvBdaEuNngP91h8PLrDNWagcdvgOfux88RQgh7lmuikdt286HgsSkRYoUsT92p5hUyUeyTmJS96Hc1JP0es1X90y+3jjgVm5sOYSsfCZfFUUhxZBCXHocCRkJKCioFV+0aFGpFMoXLYm/zq/Qb+9vUSmcEb8dZOfpBJIyjNY6/znYezaRfj/uxmBR0aR8Eb57rrZjO6spCuycDqveuz7ewFMzoFQDx23zPpGSkpLtYpZer0ev1+d7PbGxsVy8eJGWLVvapwUFBVG/fn22bNnCM888w5YtWwgODrYnXgFatmyJWq1m27ZtdOrUiS1bttCkSZNs35utWrVi7NixJCQkFMoAjvklyVcnMZqsX66OLjtgq+fp6gG3PL7sgEp1V7daOUvz5s2ZNGkSOp2OyMhI+235qampaDQadu3ahUaT/Rj4+flxxXp48PHxyfXH1lY7ZerUqdkCM8C+7rsdOAAgpEhRAoKCiD1xNNv0mwOntLQ0WrVqRatWrZg7dy7FihXjzJkztGrVCoPBcNftuJGfX/b3gDO3DdwyEq1KpXLbAFLc3zJNmQxa+QY/bYsnxPQmAPXLBDKlRwOCrv4DP/aGxDOg9oLHPoH6L16/siKEECJnHhKPQsFi0ht7hrpTTFqsWDGCg4M5fPjwHeeTmNS9YlLlpp6kKnvPVxc1KBfXyw7kPq8+nz1fjWYjcelxxKXHkWXOsk/39fJFaylOphGK+HkToL/7z0tOShXxpWwxP05cSWPTsSu0q3Fr+Y4D/yXRc/o20rLMlA+0MOHZWui1DswdZCbB0tfg4BLr4wqtoeMk8L03B6Bztpsv+AwfPpwRI0bkez0XL14EIDw8PNv08PBw+3MXL14kLCws2/NarZbQ0NBs88TExNyyDttzkny9hxmcVnbAun6Ty5Ov1v116BeowM/PL9utVDa1a9fGbDZz+fJlGjdufMvz8eeTbpl2O+Hh4URGRnLy5Em6deuW4zw1atRg2rRpxMfH59jTQKfTYTab77gdBRWt2z/Jrwt/5vzoT+y3ptnikdSUVEJ8tBw+fJirV68yZswYoqKiANi5c2ee98fmzJkznD9/3r6drVu3olar7YMY5CQv27ZdXbvT/lauXBmTycS2bdvst3hdvXqVI0eO5LmnghDu4kT8CZ76+WnOnK1PiLknAL0alubDtpXRbp8Efw4HiwlCouGpmVCijmsbLIQQotAVNCbND2fFpGq1mmeeeYY5c+YwfPjwW+q+pqam4u3tLTGpm7EnM689Vttrvrpn9tViyUfPV1vy1WxBUZQcL1QoikJyVjJx6XEkZiaiYFu/miI+RSjqWxS9xodDF1MAhRBf3S3rKEwtKoVx4kosaw9fviX5evRSCj2mbyM500TdUsF0LR7n2E5b/+22lhlIOHVtvIGR0HCAdAQoRAcPHszWg78gvV7vdR56T7jnMThpwC2drearxbVlB2w9X310knx1hQoVKtCtWzd69uzJokWLiI2NZfv27YwePZrly5ejzWc9m5EjRzJ69Gi++eYbjh49yv79+5k5cybjx48H4Nlnn6V48eJ07NiRzZs3c/LkSRYuXMiWLVsAiI6OJjY2lr179xIXF0dWVtYt2zArCq++/SGRkSWpX78+s2fP5uDBg8SePMHi+T/ySOMGpKamUqpUKXQ6Hd9++y0nT55k6dKlfPzxx/l+jby9venVqxf79u1j06ZNvPbaa3Tp0iVbXbGb5WXbpUuXRqVSsWzZMq5cuXLLqIsA5cuXp0OHDvTr14+//vqLffv20b17d0qUKGGvbSOEJ1h0aBF1vq/D6bP1CTC3QwV83LEaIx+NRPtzN/jjfWvitUoHeHGjJF6FEOI+k1tMml/OiEkBRo0aRVRUVLaY9NixY8yYMYPatWtLTOqGbMnGW8sOuKxJd2RLFucl+eqlUdt7G99cXtBgNnA+5Tz7L+/nWPwxEjKt5QX8vPyIDo6mZnhNSgeXxk/nR2KGEUVR8PHSOPw8vXkla8/EDUeu2BPNACevpPLc1G0kpBupUTKIqT1qo3dUUxQFtk6G6Y9ZE69BpeD536HRQEm8FrKAgAACAwPtfwVNvtq+9y5dupRt+qVLl+zPFS9e/JayJyaTifj4+Gzz5LSOG7fhbJJ8dZLrA2459kOutdd8de2vjL3mq4OTzeL2Zs6cSc+ePXnzzTepWLEiHTt2ZMeOHZQqVQrNtftx8voueeGFF5g2bRozZ86kevXqNG3alFmzZtm78ut0Ov744w/CwsJo06YN1atXZ8yYMfZbwDp37kzr1q1p3rw5xYoV46effrplGxaLQlBICMv/XE/37t355JNPqF27Np3btmTV0oV88NEogoKCKFasGLNmzWLBggVUqVKFMWPGMG7cuHy/PuXKlePJJ5+kTZs2PPbYY9SoUYOJEyfecZm8bLtEiRKMHDmSd955h/DwcAYOHJjjumbOnEndunVp164dDRs2RFEUVqxYccttXUK4I4PZwBur3qDz/zqjSX2GwGuJ17FP1aBH5EWY3BiOrgSNHtp+AU//AN5Brm62EEIIF7hTTJpfhRmThoeHs3Dhwhy3ExoaytatW7PFpI0bN+ann37i888/l5jUDSn2ZGb2fy1uWnfg5jIJd6JSqbLVfVUUhcTMRI5dPcY/l/7hfMp5DGYDGpWGML8wqhSrQuVilSnqWxSN+npmMyHNWpIixM+xvV4BHogOxV+v5WqagX3nEgE4G59Ot2nbiEvNonJEILOff5AAbwe9zzISrOMNrBoKFqN1vIGXNkLJerkvK1wmJiaG4sWLs2bNGvu05ORktm3bRsOGDQFrXezExER27dpln2ft2rVYLBZ7SZqGDRuycePGbIN8r169mooVK7qk5ACASnG3Yi0Odu7cOaKiooiNjSU6Otpp2232+TpOXU3nl5caUi/acXVFRq88xPcbTtL34Rg+bOe6W0XG/3GEb9Yep0eD0nzcsVqhrttoNLJixQratGlTKEFBZmYmsbGxxMTE4O3tXQgtdH+n4tJIzjRSMsSHUD/n3xJgG102MDAQ9bVeuGfj00lINxAR5E2xgOvH4UJSBldSsijqrycy2DF1iUT+5HT8hGMV9vfU3XyPnkk6Q9dfurL17FZCjP0INFt7xnz2ZDW6GBbBmo9BMUNoWXh6FkTceQAVR4qPj2fiuuP4BQbnOm9aciKvNC9HaGhogZdzplOnThETE8PZs2cpWbKkU7ctCoerYlJROCQe9XwSz3i+G4/h4YspmCwKFcID8PbScCUliwtJGQT76igVmr8B5JzhYlIml1MyKeKvp0QeznFs529+3gZSTRcwWq4nlfx1/hTzLUaId8ht38sZBhPHLqeiUqmoXDzA3mkrv/LzXfXyj7tYeeAir7UoxzMPlqLL91s4l5BBuTB//te/AUX89YX+XQrAuZ2woA8knQGNzjrewIP976vers6KgduW8aJOnTr5ikdTU1M5fvw4YC1NM378eJo3b05oaCilSpVi7NixjBkzhh9++IGYmBg+/PBD/vnnHw4ePGh/zz3++ONcunSJyZMnYzQa6dOnD/Xq1WPevHkAJCUlUbFiRR577DGGDh3KgQMHeP755/nyyy/p379/ntpZ2KTmq5M4q+yAl9pW89XFZQeu7a+3lwQy7sjW89XkRleCzdfaornp8q/KzUcqFeJ+suLYCnos7kF8ejzFlQHozY8D8GXbEnQ6+iYcX22dsdpT0P4r0Ae4rrFCCCGEuG/cPICVu/d8teSx56tFsZCUmUS6KRPwITkrHbPKiFattddy9fHKPXmbkG5N1gZ6awuceM2v5pXCWHngIsv3X+C3fy5wLiGD6CK+zHuhPkX8HdABSFFgy3fw54jr4w08PQsiaxf+tkSB7dy5k+bNm9sfDx48GIBevXoxa9Ys3n77bdLS0ujfvz+JiYk8/PDDrFq1Kluyf+7cuQwcOJBHHnkEtVpN586d+eabb+zPBwUF8ccffzBgwADq1q1L0aJFGTZsmMsSryDJV6cxXCsD4PgBt6zf3kYX/8jYa746snC2KDBbgtPsRsGIPfl60xVJ2ydGcq9CuI7JYmLYumGM/ms0KFBJ/z4ZSdZbf6Y1y6Ll9mcg5QJoveHxz6BOz/uqd4EQQgghXMtedoDsNV/ddcCt62UHco6XMk2ZxKXHcTX9KkaLEbUShBYfvNQ+lA4uQ7B3MGpV3nILFkUhMf1ayQEHD7R1o2YViwFw4koaACWCfZjbrwFhgQ7o3Z8eD0tehqOrrI+rdIQnvpGyV26oWbNmd+xYpVKp+Oijj/joo49uO09oaKi9l+vt1KhRg02bNhW4nYVNkq9OYjBZk5GOTr7a1u/qnq8ZBuv+6iX56pa0tuSri2sD3+j2PV+t/7pPS4W4v5xPOc+zC59l4+mNoECLot9y4lwMaiwsrr6VmtsmgmKBohWsvQvCq7q6yUIIIYS4z1wfcMv62HZK4aa511t66lqnWUjMTORK2hVSDCn26V5qLwJ1AaSkg07tS6hP/u4sSskwYrIoeGnUBHg7LwUUFuBNjZJB/HMuieKB3vzUr0GeSizk25mt8EtfSD5nHW+g9Wio97zHdwSwWCwkJibma5ng4GApo+KmJPnqJLYBsPSOLjtwreerycVJtetlByT56o7csuyAcueyA+561VqIe9mak2t4btFzXE67TIBXAJ1KzmbDQS+KksRvJX4g4thW64w1n4U240Dv79oGCyGEEOK+c+Npgu3cwd3PISw39HzNNGZyJf0KVzOuYrKY7PME6gMp5luMIO8gjCaFI+kpGK4NuKXKR2LRVnIg2NcrX8sVhqGtKzFv2xnefKwCpYoUcu1diwU2fwVrP3Gb8QYKU2JiIuOX7cHbL2/J9sy0FAa3q+30cQhE3khK3EmM13qiOrzswLWrHAZX13y9VnbAk2q+3k81RbXuXHbg5uTrtX/vo8MjxC2c/f1ktpj5aMNHPDrnUS6nXaZ6WA1eqrSKDQe9aKj+l02BHxBxdSt4+UKHidBpsiRe3dzGjRtp3749kZGRqFQqlixZku15RVEYNmwYERER+Pj40LJlS44dO5Ztnvj4eLp160ZgYCDBwcH07duX1NTUbPP8888/NG7cGG9vb6Kiovjss89uacuCBQuoVKkS3t7eVK9enRUrVhT6/grhqe6neFSIwnJjgvWWmq9u+pGytfly2iUOXDnApbRLmCwmvNReRPhHUD2sOhWKVCDEJwS1So2X1lpQwaIo+epAYzRbSMm0Jl8Lo+RAfr+jHipXlAnd6lCmWCHHiWlxMO9pWDPSmnit/jS8uOGeSbzaePsF4BcYnKe/vCZphWt4TmbMg1ks178gbT1THcVter56UM1X26iK6enpLm6J87hbz1eLoly/+nu7Abec3ioh3Ift+6nQRoG9gytpV2gzrw3D1w9HQaFvrRfoUupHftl+lTe0vzBP9yk+/2fvvsOjKLcHjn+3pZIKJBBqaNJLgiCCiIKAKIICiqAgJbFhgXvtAort2vhhu3IJUlSwAIqIgCAqoCAt9N6kJxCSkL51fn9MZgPSUrZkk/N5nvtcdzI7+y7b3vfMmXMs56B6M0j4DdoNdfuYRNnl5ubSpk0bPvnkk8v+/Z133uHDDz9k6tSprF+/nuDgYHr16kVBQYFzn6FDh7Jr1y5WrFjB4sWLWb169UWNC7KysujZsyf16tVj8+bNvPvuu7zyyitMmzbNuc/atWu5//77GTVqFFu2bKF///7079+fnTt3uu/JC+EDKuN8VAhX0dYJOooSN/TltGlvvjWfY+ePkWVWT14W2NTPfJh/GI0iG9E6ujW1Qmvhb7y4IZVep3MmcmnNvIsjI8+CAgT5GV1yVaon56RX9PcfMLULHPxF7Tdw10dwT5I0ehXlmpQd8IALs1D93Fx2QOtcaHOUl8zX8h98NRgMhIeHc+bMGQCCgoI8fjmGp9ksdhSbBatDT0GB5384HQ4HFouFgoIC9Ho9VrsDxaYWgbeazdgu+Pe3WSwoNgs2i52CgvL/fqoM/vn6CfdRFIW8vDzOnDlDeHg4BoN7PwNrjq5h8ILBnMo+RZApiP/2+ZTUlA7M/30Tc0yf0MmwW92x3YNqYy0/F18+Jtzm9ttv5/bbb7/s3xRFYcqUKbz88sv069cPgM8//5zo6GgWLlzI4MGD2bNnD8uWLWPjxo20b98egI8++og+ffrw3nvvERMTw5w5c7BYLMyYMQM/Pz9atGjB1q1bmTx5sjNI+8EHH9C7d2+eeeYZAF577TVWrFjBxx9/zNSpUz3wLyFE+VQZ56PeJvMZ36e9hvr8fHUtodNhNpsBsFjV9Y7Nob/oRKI32B12ssxZpOenk2/LB8DoiAb0hAVUoXpIDH4GNStVG//lGBQris1Odm4eBuXaWayKonAuMw/Fbic4qGz/Dp6ek16Www5r3off3yrsN3BdYb+B5p4fixAlJMFXD7BeEHz1VMMtq9czX7War74xkalRowaAc8Jb0dkdCmfOF6ADDLluKHp+DYqikJ+fT2BgIDqdDqvdwZksM3od+OVfPJ58i51zuRb8jXps5/2vcEThSf98/YT7hYeHO7+n3MGhOHhv7Xu8uPJF7IqdptWaMm/gPJZuNbJj9fcs8f8v1XRZYAqGvlOg9b1uG4somezsbLKyspy3/f398fcv2XflkSNHSElJoUePHs5tYWFhdOzYkXXr1jF48GDWrVtHeHi4M/AK0KNHD/R6PevXr+fuu+9m3bp1dO3aFT+/ogVhr169ePvtt8nIyCAiIoJ169Yxbty4ix6/V69el5RBEKIyqmzzUW+T+Yzv015Dk3+Acy1hylPXErYL1hfeWO8AWOwWsi3Z5FpyL8rADTIFYbedxeYARxU/LBnZVzlKkYw8C7lmOwXpRjICr51AY7E5OJOt/hsY8wLIdMH73N1z0ivKToXvEuDIKvV2myFwx3vgF+z5sQhRChJ89YALLwvwc3vwVbucvJxkvhp9I1NRp9NRs2ZNoqKisFqt3h6O25mtdh7+cA0ACx/vTEiAZ7NfrVYrq1evpmvXrphMJnadPM8rP2yhRlgAc0ZffObyr8NpvPLbTppEh/DpA009Ok5xef98/YR7mUwmt2YXpOen89DCh/hx/48ADG01lE/v+JSk348RtOYNvvBbpO4Y3UrNLqjWyG1jESXXvPnF35kTJ07klVdeKdExUlJSAIiOjr5oe3R0tPNvKSkpREVFXfR3o9FIZGTkRfvExsZecgztbxEREaSkpFz1cYSozCrbfNTbZD7j+7TXsFazOF75YRsRwX7Mf0T9XUzLMfPID+vQ63Usf7qrxwLsOZYcftr/E9/u+pZdZ3c5t9cNq8vA5gO5u+ndVA+uzrDP1nMyM58PBrcltlZ4sY69YeMxpq0+zC3XRfHynU2uuf//rdjP4u1n6NEsmhfaNSjtU3Jy95z0ig7/DgsSIPeM2m/gjveh7RDPj0OIMpDgqwdoWahGve6SepaupjXcstq8nPlqKwy++vlG8FVjMBi884PiYQEBkGGGPIudPLue6gEBHn18g8GAzWYjICAAk8lEljWLk9l2IkINBPxjLAaTPyez7YQE2y/5m/COf75+wndtPLWRId8P4ej5o/gb/Pnw9g9JiEsg6ac/6LLhX3Qw7lN3bD8Ser0JJu9kjogr2717N7Vq1XLeLmnWqxCi/Kks81Fvk/mM79NeQytGTmbb0RlxrhdCFAMns9U1qcHk79byf4qisOHkBpKSk/h659fkWnMBMOlN3NPsHhLiErgl9hb0uqIxHD1vJTXbTkBAYLHXONERoZzMtrMjJe+a9ymw2pm7+TTZBXZ6ta7jm+sohx1WvQ2r3gEUiGquJgJUv87bIxOixCT46gFa2QF3lxwAMBZmvlq9nPmabyksO+Ajma+VUUSQH3mWfDLyrNSr6t2xZBV24Ay7zOUzfqUoLC+EuDpFUVh8djGzP5+N1WGlYURD5g2aR+0qzZk1axoD/55EpD4HiyEYv7s/hpb3eHvI4gpCQkIIDQ0t0zG0ywdTU1OpWbOmc3tqaipt27Z17vPPS6FtNhvp6enO+9eoUYPU1NSL9tFuX2sfr1zCKIQQokIwF64TLgywXlj+Lt9qd0vwNbMgky+3f0lSchLbU7c7t19X9ToS4hIY1mYY1YOrX/a++ZbCBtUlSFaqX02ttf/3uWs35vt5VwrZBTZqRwRyQwMvL/ZKI+s0LBgNR/9Qb8cNg95vS78B4bN8oyCnj7vcj4G7OMsOeLnmq9nZcEveYuVVeJAa6MzIs3h5JHA+Xw2+hl6m/IH2ubmwcZ0QovTOF5zn/u/vZ/rJ6VgdVgY0G8Ca4RtYs8OfH98bxYijzxKpy+FsSDP8Hv9DAq+VQGxsLDVq1GDlypXObVlZWaxfv55OnToB0KlTJzIzM9m8ebNzn19//RWHw0HHjh2d+6xevfqiy6VXrFjBddddR0REhHOfCx9H20d7HCGEEKKktHWC/wWJP34GPdpFp9ra1BUUReGPY38wfOFwYt6P4YmlT7A9dTsBxgAebP0gqx9azZ7H9/CvG/91xcArFPVICSxBg+q6kWrg8Xy+lcxrrOHmbToBwIC42m6/+tblDv4CU7uogVe/KnDPdLjrIwm8Cp8mma8e4MnM16KGW16u+aqVHSjBj4nwrIggtSHKtX64PeF83pUzX02S+SqEy2xN2cqgeYM4mH4QAwbeuvUdog33kPDhMiZZ3ydOfxCA09cNp+agd8Eol7BXFDk5ORw8eNB5+8iRI2zdupXIyEjq1q3L008/zeuvv07jxo2JjY1l/PjxxMTE0L9/fwCaNWtG7969SUhIYOrUqVitVsaMGcPgwYOJiYkBYMiQIbz66quMGjWK5557jp07d/LBBx/wf//3f87Hfeqpp7j55pt5//33ueOOO/j666/ZtGkT06ZN8+i/hxBCiIrDYr002Umn0xFoMpBrsZPvguDrubxzfL7tc5KSk9iTtse5vWVUSxLjEnmg9QNEBEYU61h2h+IMGJdkvRzkZyQqxJ8z2WaOnssjPMjvsvudzMznz0NpAAyMr13s43ud3Qa/vQ5/FM4bpN+AqEC8npb4ySefUL9+fQICAujYsSMbNmy46v5TpkzhuuuuIzAwkDp16jB27FgKCgo8NNrS0YJGfgb3n3HSar7aHN7LfLXZHc46tyU5kyc8y5n5muv9hg5a5uvlgq/+kvkqRJkpikLS5iRumH4DB9MPUjekLiOrf8zide1Ys3g2c2z/Ik5/EKspBOXez6l5/4cSeK1gNm3aRLt27WjXrh0A48aNo127dkyYMAGAZ599lieeeILExESuv/56cnJyWLZs2UU14ubMmUPTpk3p3r07ffr0oUuXLhcFTcPCwli+fDlHjhwhPj6ef/3rX0yYMIHExETnPjfeeCNz585l2rRptGnThvnz57Nw4UJatmzpoX+JK6sMc1IhhKiIijJfLw5vaJf0lzb4qigKvx35jSELhhAzOYZxy8exJ20PQaYgRrYdybpR69j+yHae6PhEsQOvUNScGkq+Xq5XVc3+PJp+5dIDCzafQFHghgaR1In0kWzRrJMw646iwOv1o2H0LxJ4FRWGVzNfv/nmG8aNG8fUqVPp2LEjU6ZMoVevXuzbt++SjroAc+fO5fnnn2fGjBnceOON7N+/n4ceegidTsfkyZO98AyKR8tC9WTZAW9mvhZckKEoma/lV3nKfNVqvoZeruarUTJfhSiLXEsuj/70KF9s/wKAm2uOJih/CL8dy+IF41RG+i0DwBETj2nQDIio78XRCnfp1q0binLlE7M6nY5JkyYxadKkK+4TGRnJ3Llzr/o4rVu3Zs2aNVfdZ9CgQQwaNOjqA/awyjInFUKIikgr8/fP4KtWhkC7xL+4zuSeYdbWWUxPns6B9APO7e1qtCMxPpEhrYYQ6l/6eusXBoP/OeZrqVc1mI1/Z3A0Lfeyf3c4FOZvVksODIqvU+oxelL0+a0Ypz8F+RngHwp3fQgt7vb2sIRwKa8GXydPnkxCQgIjRowAYOrUqfz000/MmDGD559//pL9165dS+fOnRkyZAgA9evX5/7772f9+vUeHXdJWTzacKsw89WLNV8LyvBjIjwnwlnztfxkvl4t+OrtUhpC+KLdZ3czaN4gdp/djb/SgI6hr/P34VDq6I7wnd9HtNIfVnfsNAZ994lgvPzla0JUdJVlTiqEEBWR5QrBV2fmq+Xama8OxcEvh38hKTmJH/b+gNWhrk+q+FVhaKuhJMQlEB8T75LxauMJMOlLXI+1XuTVM183/J3OsfQ8qvgbub1VOW9mabeiXzmRGw5/ot6u2RYGzYTIBl4dlhDu4LXgq8ViYfPmzbzwwgvObXq9nh49erBu3brL3ufGG2/kyy+/ZMOGDXTo0IHDhw+zZMkSHnzwwSs+jtlsxmw2O29nZ2cDYLVaL2oI4U75ZvVxjHqd+x/ToX6RW+0Ojz2/f8rJV/+9/Yx67HYbdtfVNwdwPi9vPb+KIiRAnYycyynw+L/lP19DLfu2iunSz4jO+Z5WMJstvlcwvgKSz6BvmLNzDo8vfRyzOYjavIDR3JmjBXCHYQPv+ycR4MhFCQjH3vdjlCa9QQEq2GtqtVpRFDsOx7V/iBTF7pwblPZ+niSfP9epTHNS4TryW+j75DX0fdprl3eF9XZAYTA2p8B8xdf5VPYpZm+fzaxtsziSecS5vUNMB0a1HcWg5oOo4lfloscrq+zC9XKgyVDiY9YOV8tC/Z2Wc9n7frPxGAC3t4zGpFPK7/s78xiG7xMwnFIbeVrjR0GPSWrZq/I6Zg8ryXwUXDOXLen9bDZZmxeX14KvaWlp2O12oqOjL9oeHR3N3r17L3ufIUOGkJaWRpcuXVAUBZvNxiOPPMKLL754xcd56623ePXVVy/Zvnr1anbv3l22J1FMO9J1gIG8nCyWLFni1sc6nQdgJDe/wO2PdSWp+eoYjIrdrWNYsWKF245dGRw9q74vDx4/zZIlJ70yBu01PJFqAHTs27EV/YktF+2TbwPtq+rHJUsxSTJ1uSGfwfLJ7DAz/eR0fklbS5jtPqrb7gJM+GHh/6p8SR/bL+CAc8GN2Vz/UfIPOuCgd34v3C07O5tDJ/UEBIdcc9+C3GxWFBwiJCSk1PfzpLS0NI8+XkVWmeakwvXkt9D3yWvo+3bu2QsYSEu9eF2Tl62uMdau30TewaIrQ+2KnS1ZW1h+bjmbsjbhQM2cDdIH0S2yG7dVvY3YwFg4BatPrXb5eI/nABhRbJYSr5e1++4/lXHJfQvs8NM29TnHFBxlyZKjLhqxa9XI3Ey7Y0no7XlYDEFsqZtAiiMelq/09tDKlZLMR8E1c9mS3m/dKZmPFpdXyw6U1O+//86bb77Jf//7Xzp27MjBgwd56qmneO211xg/fvxl7/PCCy8wbtw45+2TJ0/SvHlzunbtSv369T0ybt3OFNi3nepVI+jTp4NbH+tIWi7/2fYneqOJPn16ufWxrmTXqSzY+hchQQH06XOzy49vtVpZsWIFt912GybTpZepi+IJ3n+WLw9uwRAYRp8+nTz62P98Dd/ZsxryCujetRNt64RftK/Zauf5jeoP8a09ehIS4FNfWxWSfAbLrwPpBxi84H4Op0ZSyzoVA2rzh7618/iPYzLB6WqAx9pxDH+a4+jR8/YK/Rqmp6dzZM1hgkLCr7lvXnYmt93UgMjIyFLfz5P+/vtvjz6euJivzkmF68hvoe+T19D3aa9hvQaN4OgRYuvVoU+fFs6/zzu7mcPZ52jeqg192sZw7PwxZm6byextszmRfcK5X+fanRnZbiQDmg4gyOT+BlUb/86AHRuJCAmmT58uJbrv+Xwrk3f8RpZVR7cePQnyK1obzU8+iWXDLmKrBvH4fZ3R6cpZVqLNjP7XSRiO/A9Q+w3Y+35Kyoa98jm8jJLMR8E1c9mS3q9TvcbFGpvwYvC1WrVqGAwGUlNTL9qemppKjRqXr00yfvx4HnzwQUaPHg1Aq1atyM3NJTExkZdeegm9/tKUOH9/f/z9izo2Z2VlAWAymTz24XagjsvfZHD7Ywb6q/X6rHaH1768bIr6JR/g597n68nXsCKqHqpOLM7nW73276i9hllqeitVQwIvGYvBUPQ1pej08pqXI/IZLF/m757P6O9exj9vGNUcbQBoUD2YD1seosXmCegsORBUFe6eBvVvRlmypMK/hiaTCZ3OgF5/7eaPOp3B+e9R2vt5UkV+3TytMs1JhevJ6+f75DX0ffbC9Wegn/Gi11ILTG44uZWZ+x9l2cFlKKgZsFUDqzKszTAS4hJoVr2ZR8drvcJ4i6OayURYoInz+VZOZVlpVjPQ+bfvt5wGYGD7Ovj5lbM6/ulHYN5DcHqreruw34BR0QF75XN4GSWZj4Jr5rIlvZ/RKIlRxeW1C3j9/PyIj49n5cqi1HKHw8HKlSvp1OnyWXh5eXmXTGYNBvVNcbUOvt6mNdzy80jDLfWL3LsNt9TnG2As3peE8I6IIPUH2dsNt+wOhWyzGny9XMMtvV6HsbDOq0WabglxCYvdwpjFY0mY+wNhOf8h0NEGP6OO57rXZUWj72i5bpwaeK3XGR75Axr38PaQhShXKtOcVAghKiKz7dL19uGMw+xL3wnA/zbPYOnBpSgo3Bp7K18N+IqT404yuddkjwdeoajhltYQrKTqVy1sunWuqOnW32m5bPg7Hb0OBsTVLvsgXWnXQvhfVzXwGhgB938Dvd6QRq+iUvFqmHrcuHEMHz6c9u3b06FDB6ZMmUJubq6z0+ywYcOoVasWb731FgB9+/Zl8uTJtGvXznmJ1/jx4+nbt69zwlseaV3aTZ4IvhYuBGwOBUVRvHKpQYG1sHtjKX9MhGeEB6uBznyrnQKrnQCTd16v7IKi4G/YZYKvoDZvs1nsWG2yoBXiQkczj9Jv9oucTbmVMEXN0Lu5STXeuimAmBUPw5ldgA66/htufh4McnZaiMupLHNSIYSoiCyFwVejQeHbXd+SlJzEL4d/IdLyBCH0IsRUlcdufI7RcaNpFNnIy6O9YL1cymYWdasGs+3EeY6ey3Vum79ZLaNwU+Pq1AgLKPsgXcFaAMtfgo3T1dt1boCBn0FYOQsOC+EBXl2F3XfffZw9e5YJEyaQkpJC27ZtWbZsmbPhwbFjxy7KKnj55ZfR6XS8/PLLnDx5kurVq9O3b1/eeOMNbz2FYtF+DPyM7g++Xni2z+ZQMBk8H3zN135MPPB8RemF+Bsx6nXYHAqZeVZqhHlnsXg+Xw2+BvkZrniCws+oJ89ix2IvXqdHISqDL7Ys5vnvNmKyDsEEhAcr/OfueHrZfkf37b/AmgvB1eGeJGh4i7eHK0S5VlnmpEIIURGdyUkH4MMNkzm9YQYAOnTUDatBRjo82eHfPNejuTeHeBEt+BpYyuQXZ+Zrupr5ancoLEhWg6+D2peTwOa5QzBvOKTsUG93GQu3vAQGKS0gKievp8CMGTOGMWPGXPZvv//++0W3jUYjEydOZOLEiR4YmetYvVB2ANTSA95IZiw6kyeZH+WZTqcjPMhEWo6FjDyL186QavVer5T1CkVZ49olRUJUZvkWM/d/8T+SD9TERAfAwb0dqjPhtmZUWfkCbJ2j7hjbVQ28hly+ZqUQ4mKVYU4qhBAVRYGtgG92fsO7B94lJeM2qtCDXOt5YiJjGNl2JKPiRvHVunz+t+owFpu3R3ux/DKul+tGamUH1MzXPw+mcfp8AWGBJno0i3bNIMtix3z48Sm4sN+AlL0SlZzXg6+VgbWw/qpHyg5cEHy12B0E4vkAaEFhgKy0l1EIzwkP8nMGX71Fy3wNDbhy8FU7cWGR4Kuo5H7evZ8x3/yJ1dwQPRAZmsGs4bfT2nQGPu8JZ/eCTq+WGOj6byhmgX4hhBBCCF+w88xOkjYn8cX2L8goyACgOncAMDpuOG/3/xqjXg1zBJr2A0XJQeVFflkzX6sFA0U1X+cVlhy4q02MdxOgrPmw9DlInq3ertcFBkyH0JreG5MQ5YQEXz3A7MGyA6YLLomzeak5kbmMPybCcyKC1IBnphebbmnB16tlvvoXfnasXmwkJ4Q3ZeZZeOLblazZ6wCicOiyue8Gf96+cwj6bXNgyTNgy4cqNdRJbuxN3h6yEEIIIYRL5FpynbVc151Y59xeN7QunYM6ozfcwR8Hs4mr1doZeIWi9Wh+OQu+FpSx4Va9wszXU5n5pOWY+XlXCuDlkgNn98G8h+DMbtR+A8/Azc9JvwEhCsknwQM82XBLr9eh14FDUWu+eoPWvVHKDpR/4UFqh8lykflajLIDkvkqKqM/Dpxh1OdrMVvVz4hflc3MHX4v7aNqw8KHYce36o4Nb1Uv66pS3YujFUIIIYRwja0pW5m2eRpzdswhy5wFgEFn4K7r7iIxPpFudbrx87KfWZCmrmn+WeZPW4+W18zX0q6Xq4f4E2gykG+189/fDmGxObguOoRWtcJcOczi2/oV/DQOrHkQHAX3TJN+A0L8gwRfPUALGJmMnml+ZTLoMdsczqCvpxXYJPjqK8pD5mtWgRZ8vfLXkZY1Lg23RGWz/+xJhs/6E7s9GIvuKJ1bHuPzeycSeO4gTLsZzh0EnQFufQk6jwW9lHsRQgghhO/KNmfz1c6vSEpOYtOpTc7tDSIaMLrdaB5q+xA1Q9TL2K1WdR2hrbf9/7H+DHQGX8tXAoc2ntKul3U6HfWqBrE3JZsv1x8F1KxXnc7DzbYtuerVV85+AzcX9hsoB3VnhShnJPjqAVoQ1N8Dma9QFHy1eekSbe3HxF9qvpZ7EYWZr+m53s98vVrZAWfw1SZlB0TlsfroaobOWIbB3hmb/gSvDwxhZLu3YPNMWPo82M0QEgMDZ0C9Tt4erhBCCCFEqSiKwqZTm5i2eRpf7fyKXKvaSMqkN3F3s7tJiEvg1thb0esuv750lvn7Z+Zr4WX92pWZ5UVZa74CzuCrxebAqNfRv10tVw2veFJ3q2UG0vap/Qa6vQA3/Uv6DQhxBRJ89QBPlh2AoqZbXst8lZqvPqM8lR24avBVKzvgpfe0EJ7kUBy8++e7TFoxn+rmVwAHH9x3PQOuawTzR8Ku79QdG/eE/lMhuKo3hyuEEEIIUSqZBZnM2T6HpOQktqVuc25vUrUJiXGJDGszjOrB1y6npK0R/pn8E1CYwFHear4WBV9LHx+oXzXY+d+3NI2iWhX/Mo+rWBQFtnwBS54t6jcw8DOo38Uzjy+Ej5LgqweYnWUHPBR81Xu3OVFZa9gIzykXZQe0mq8BV6n5apSar6JyOJd3jmELh7F0/2/EWD4B4IEb6jCgOvC/rpBxBPRG6D4ROo2RMgNCCCGE8CmKorD2+FqSkpP4dte35NvyAfA3+DOoxSAS4hK4qe5NJbqE3my9/JWmWkOr8lbztawNtwDqVg1y/vegeA812jJnw+JxF/Qb6A53/0/6DQhRDBJ89QAtCPrPyyDcxVSY+WpzeCdQpf34BXgo2CxKLyLYxzJfJfgqKrD1J9Zz7/x7OXb+GNXsj2NUoqgdHsCEqHXw2QSwWyCsDgycCXWu9/ZwhRBCCCGK7VzeOb7Y/gVJyUnsPrvbub1lVEsS4hJ4oPUDRAZGlurYV8p8DSynDbdc0SOlcVQIANWq+HFL0yiXjOuqUnaoZQac/QZehs5PSyKAEMUkwVcPsHo481Urb+CtzNcCyXz1GVrN1/KQ+Xq14Ku/UXtPS/BVVDyKovDh+g95ZsUzWB1WGgT3xJ52O6HksrD6bPyW/6zueN0d0O9jCCrdwkQIIYQQwpMURWHV0VUkJSexYPcCzHYzAEGmIO5rcR8JcQncUPuGMjeKKqr5evH6U1uPlruyA5ayr5evrx/BpH4taFkrzL3lDRUFNs2AZS+o/QZCa8GAz6TfgBAlJMFXD9DOxPkZPNN9UKv5avNWzVcXnMkTnqGVHfBm5mtWgQ2A0KsEX7Vsbsl8FRXN+YLzjFw0ku/2qHVc72l6H2nHEgnX7WBmlU+JPH4a9Cbo+Rp0fAQ83cVWCCGEEKKEzuSeYdbWWUxPns6B9APO7W1rtCUxLpEhrYYQFhDmssfT1giX1Hx1Zr6WrzVEfuF4ytIjRafTMaxTfReN6AoKsuDHJ2HX9+rtJr2h/6eSCCBEKUjw1QO0bD0/T2W+ervmqwvO5AnP0Bpunc+3YncoGPSeD+wUq+yAURpuiYpny+ktDJo3iEMZhzDpTbzf831yz3XHmvkJz/t/jclqg/B6MGgm1Ir39nCFEEIIIa7IoTj45fAvJCUn8cPeH7A61Dl+Fb8qDGk5hMT4ROJj3DOfsTgzXy9f87W8Zb46G1SXoear253aAvNGFPUb6PGK2m9AEgGEKBUJvnqA9mPg1ssBLqBlvlq9VPNVO7MYUIbujcIzwgszXxVFvfxfqwHrKYqilCz4KpmvogJQFIVpm6fx1LKnMNvN1Aurx7eDvqVKfjSnfnqIHqZkdcdmd8FdH0FguFfHK4QQQghxJaeyTzFzy0w+2/IZRzKPOLd3qNWBhLgEBrccTBW/Km4dw5VqvgZcsIbwVqLJ5TiTlYzlMPiqKLBhGix/ubDfQF0YOEP6DQhRRhJ89YCisgOeCr6qj2PzVs1XKTvgM0wGPSH+RrLNNjLyLB4PvuZZ7Ngd6vv0asFX7cSFZL4KX5djyeGRxY8wZ8ccAO5sciez+88mNHUf6XO601x/FqvOhOn2t+D60ZJdIIQQQohyx+6ws+zgMpKSk1i8fzF2RV3/hfmH8WDrB0mIT6B1dGuPjMWhXLnB9YWZpWabnSC/8hH+0NbLgX7lLFkpPwN+GAN7F6u3m96p9hsIjPDuuISoAMrHt08Fp5Ud8FTDLT8v13w1OzNfJfjqC8KDTYXBV8833dLqvZoMuqtmSkvmq6gIdp3ZxcB5A9mbtheDzsBb3d/iX53Gol/7MY5fJhGFnWPUIPSBOYQ3bO/t4QohhBBCXOTY+WPM2DKDGVtmcDzruHN75zqdSYxPZGDzgQSZgjw6pguXB/7/WH9emFmabyk/wddyWabvxGaY/xBkHivsN/A6dHxYEgGEcJHy8e1TwVltlz8T5y5Grearw0s1X7UaNuXpx0RcUUSQH8fT88n0QtOtC0sOXK3Lqb9Bq2MswVfhmz7f9jmPLH6EfFs+MSExfDPwG7pUbQpzB8PBFeiBRfZOGO76gDsaXuft4QohhBBCAGC1W/npwE9M2zyNZQeXoaCuMSMDIxneZjij40bTvHpzr43PdsGS95/rbb1eh59Rj8XmKDd1Xx0OBbOt7A23XEZRYN0n8MtEcNggoj4MnAm14rw9MiEqFAm+eoDFww23nDVfvZQlqBUQl5qvvkFruuWNzFct+Bp6lZIDIJmvwnflW/N5YukTfLblMwBua3AbX97zJVFpB2FqF8g+jRk/JlqHcabRfXzWvomXRyyEEEIIAYczDjM9eTozt84kJSfFub1b/W4kxiVyd7O7CTAGeHGEKm15oNOpV9P9U6DJgMXmcPYl8Tat5ACUg4Zbeemw8DHYv1S93byf2m8gIMy74xKiApLgqwd4uuGW9jg2LzTcUhTlguBrOTiTJ64porDpVkau5zNfswvLDoQGXD346qz5KsFX4UP2n9vPoHmD2J66HR06Xu32Ki92eR7Dn1PgtzdBcZAZVJ/BGY9w0q8By+9pddUMcCGEEEIId7LYLSzcu5Ck5CR+OfyLc3tUcBQPtXmI0XGjaVy1sRdHeCktpupn0F92HhVoMnA+3+pco3qbVnIAvNxw69h6mD8Ssk6AwR96vwntR0mZASHcRIKvHqBlvl7uTJw7GAu7OFq90HDLalfQqh2Uy+6N4hIRzsxX75YduBot89UsZQeEj/h217eMXjSabEs2UcFRzL1nLt2jWsGcQXD4NwByrxtI9919OaeYeLNPM2qGBXp51EIIIYSojPaf20/S5iRmb5vN2byzAOjQcVvD20iIS+Cu6+7Cz+DZxrzFpZUd8L/CVaZadml5KTtQYCu6Klav90Kg0+GAtR/AytdAsUNkQxg0C2p6pkGaEJWVBF89QKtTeaUfBFfTGnt5o+HWhT9qAeWte6O4rAgvlh3QGm4VN/jqrVIaQhSX2Wbm38v/zccbPwaga72ufDXgK2LOHlDLDOSkgjEQ5Y73SNzciHPWc9zQIJLB19fx8siFEEIIUZkU2ApYsHsBSclJrDq6yrm9ZpWajGw3klHtRhEbEevFERaPtjzwu0Lij7YGL2+Zr16p95qbBt8/AgdXqLdbDoS+U8A/xPNjEaKSkeCrB1g9XXag8AyazQsNt8yFP2o6necajImyiQhWA5/eaLiV5az5evWvImfZAcl8FeXYkYwj3Dv/Xjad2gTAC11eYNLNEzGumQyr3gYUqN4MBs3im7+D+PPgDgJMet4e0No7mQ9CCCGEqHR2ndlFUnISX2z/gvT8dAD0Oj19GvchIS6BPo37YNT7TphAC75eM/PVUj6CrwXeak7995+wYBRknwZjANz+DsQNkzIDQniI73yr+rCisgOearjlvUCVVsg8wGiQ2oU+ItybZQeKmfnqLw23RDm3aN8ihi8cTmZBJhEBEXxx9xfcUTMevhwAf69Rd2r3ANz+Lin5et74Sc0w+XfP66hXNdiLIxdCCCFERZdnzePbXd+SlJzE2uNrndvrhtVlVLtRjGw3ktqhtb04wtKzXqvsgKl8lR3QxuGxZlsOO6yZDL+r/Qao1kQtMxDdwjOPL4QAJPjqdoqiOGuv+nmq7EBhbVmbF2q+at0bA0yS9eortIZbmd4oO1Dcmq+FJxSskvkqyhmr3cpLv77Eu2vfBaBjrY58M/Ab6qUdhE87Q14amILhzv+DNvehKAovf7WZbLONNnXCGdG5/F/OJ4QQQgjftDVlK0mbk/hyx5dkmbMAMOgM3HXdXSTEJdCzYU8Met/u02FzqGvfK621tSbQZmv5WEdoma8eKUmYcwa+S4DDv6u32wyBO94DPznxL4SnSfDVzS5seuWxzFe9F2u+erOGjSgVbzbcyiooLDsQULyar5L5KsqTE1knGDx/MH8e/xOApzs+zdvd38Bv9XtqhgEKRLdUswuqqZ2Bf9x+ml/2pGIy6Hh3YGsMUm5ACCGEEC6Ubc7m651fMy15mrMUEkCDiAaMbjeah9o+RM2Qml4coWtds+xAect8tXgo8/XwKjXwmpMKpiC4431oO8S9jymEuCIJvrrZhZf+e6oGqhbktXqh5qt2Ji9Agq8+I7ww8zUjz4qiKB4tF5GVX7yyA9p72izBV1FOLD+0nKHfDSUtL41Q/1Bm3DWDAbVugC8GwLHCy/niR0Dvt8AUCMDRc7m8smgXAGNuaUyTaGluIIQQQoiyUxSFTac2MW3zNL7a+RW51lwATHoTdze7m4S4BG6NvRW9ruJdnWhzlh24/PozoLwFX91d89VhV3sNrHqHC/sNENXUPY8nhCgWCb662YXd2T1fdsALNV8Ln6+/BF99hpb5arE5yLfaCfLz3NfC+eKWHTBKwy1RPtgddl5d9Sqvr34dBYV2Ndoxb9A8GqYdgqldID8d/ELgrg+g5QBsdge/7kph7oZjrNp/FkWBpjVCeLRbQ28/FSGEEEL4uPMF55mzYw7TNk9jW+o25/YmVZuQGJfIsDbDqB5c3YsjdD+tmsCVyw6o2wvKSfDVrQ23sk6r2a5av4G4YdD7bfALcv1jCSFKRIKvbqbVqNTr8NjlpcbC4KvVGzVfrVLz1dcE+RnwM+ix2B1k5Fk9GnzNLmy4FVrM4KvUfBXelJqTypDvhvDrkV8BSIxL5IOe7xGw6h1Y+6G6U802MHAmpwwxfL1iP99uPE5KVoHzGJ0bVeW1fi09djKuonA4HGRmZhZ7//DwcPR6+TcWQghR8SiKwtrja0lKTuLbXd+Sb8sHwN/gz8DmA0mMT+SmujdVmubHvlp2wOVXih5cCd8lqv0G/KrAnVOg9SDXPoYQotQk+Opm2mXSnlxoazVfvRGocuuZPOEWOp2O8CATZ7LNZORaqBUe6LHHPl9QsoZbUvNVeMvvf//O/QvuJyUnhWBTMP+7838MrdsVvrgHTmwAwNEhkVX1nmTO4hR+3bsXrfJLZLAfg+Jrc3+HutSvJg0OSiMzM5PJi7cQEHztUg0FudmMu7MdkZGRHhiZEEII4Rnn8s7xxfYvSEpOYvfZ3c7tLaq3IDE+kQdaP0BkYOX77dPKDlxpva3VVi2wlI/gq3alqMuCr3Yb/PYG/DFZvR3dqrDfQCPXHF8I4RISfHUzLQDqqWZb6mNpZQek5qsonoggPzX46sGmWzYHFBReJ1TczFcJvgpPcygO/vPHfxj/23gcioMW1Vswb9A8mp07opYZKMjE4R/K0gYv8+b2xpxcvd153xsaRDKkYz16tYi+Yh0yUXwBwSEEh4Z7exhCCCGExyiKwqqjq0hKTmLB7gWY7WYAAo2B3NfyPhLjErmh9g2VJsv1cq6V+Vruar46G265ID5w/iQsGAXH1qm324+EXm+BKaDsxxZCuJQEX91Mu/TfU8224MKGW97IfNXO5Mnlnr7kwqZbnpKnVhxAp4MQ/6t/FWmfH2+U0hCV17m8czz4/YMsPbgUgGFthvHfXlMIXvUO/PVfAI74X8dD2Y9xdEt1IJ/wIBMD42pzf8e6NKxexYujF0IIIYSvOpN7htlbZzN9y3T2n9vv3N62RlsS4xIZ0moIYQFhXhxh+XHtmq+Fma/W8pHE4bIrRfcvh+8fvqDfwIfQ8h4XjFAI4Q4SfHUzizfKDhQGqrya+SpZXj5Fa7qV6cHM1/zCk88h/kb016iHLJmvwtPWHV/HffPv43jWcQKMAXzS5xNG1LsF5Yt74FQyANNtt/N2wf1YMXJ9/QiGdqxH75Y1JPNfCCGEECXmUBysPLySpOQkFu5diNWhJkVU8avCkJZDSIhPIL5mfKXOcr0cm6L+e1zpKqNyV/O1rMFXuxVWTrq438CgWRDZwDUDFEK4hQRf3czixbID3qj5qv2YBPhJ8MGXRASrwdeMXM9nvoYFXb3kABR9fix2B4qiyKRTuI2iKEz5awrP/vIsNoeNxpGNmX/vfFqlHcb26U2YrNlkKsH82/oIG/w6MrRDbYZ0rEuT6GvXIhVCCCGE+KfT2aeZuXUm05OncyTziHN7h1odSIhLYHDLwVTxk6tprsR2zcxXdXtBeQm+FpYd8C9N8DXzGMwfCSc2qrc7PAw9XwOjvwtHKIRwBwm+upmWqacFRD2hqOGWNzJfC8sOSOarT4lwlh3wXOZrnk39TFyr2RZcPJmy2B1SP1O4RWZBJiN/GMn3e78H4N4W95J0+0cULH4N3Z7PMQGbHY0ZbxzHvT078dH1dZ1NHIQQQgghisvusPPzoZ+Ztnkai/cvxq6oAbkw/zAeaP0ACXEJtKnRxsuj9A3Xqvka6Cw7UD6Cr1rDrRJnvu79CRY+BgWZEBAG/T6BZn1dP0AhhFtI8NXNtOxTPw8Gi4xawy2v1HzVGm5JzVdf4pWyA4WZr6EB1w6+XjiZstoVrlEiVogSSz6dzKB5gziccRg/gx//1+v/6Bt+E5kf3k5d80EAkhx9ye70At/c0oSQYrxvReXjcDjIzMws9v7h4eHo9fJ7KYQQlcWx88eYsWUGM7bM4HjWcef2znU6kxCXwKAWgwgyBXlxhL7HWphvdMXMV79yVnbA2XCrmPEBmwVWTID1n6q3a8XDwJkQUc9NIxRCuIOEMNzMGXz1YOarnxdrvpptWvBVssF8iTcabmk1X4uT+Xph2Q6LzQFyZY1wEUVR+N/m//HUsqew2C3UD6/P9Du+IeOPtUQcuY0qunzSlSosrD+eO+8ZTs2wQG8PWZRjmZmZTF68hYDga5ehKMjNZtyd7YiMjPTAyIQQQniL1W7lpwM/kZScxNIDS1FQ12iRgZEMaz2MhPgEmldv7uVR+q6izNfLrz+1KzK1oKe3lajhVvoRmD8CTm1Rb3caA90ngtHPjSMUQriDBF/drKjsgCcbbnmx5qvFRd0bhUd5I/PVWfO1GMFXg16HQa/D7lCk6ZZwmWxzNg8vfpivdn4FQN/G93BrxAukf/EWg3S/gA72+bfCMOgzRja6zsujFb4iIDiE4NBwbw9DCCGElx3JOML05OnM3DqT0zmnndu71e9GYlwidze7mwBjgBdHWDFcq+arlmGqlcfzNmePlGutl3cthEVPgDkLAiOg/6dw3e3uH6AQwi0k+OpmFmfZAQ8GX501X71RdqCw5quUHfApEcFeyHwtrPkaWozgK6gZ3fkOu1fe16Li2XlmJwO/Hci+c/swYGL4df8l+5AfvfaOoJn+GA50nGz5KNfd/RoY5KdSCCGEENdmsVv4Ye8PJCUnseLwCuf26kHVeajtQ4yOG02Tqk28OMKKx1Z4safP1Hy9Vpk+awEsfwk2Tldv1+kIAz6D8DoeGqEQwh1kRelmWtMrT2a+mpw1X73QcMtWhu6NwmvCCzNfPdtwS/3/4mS+gnoCI99qxyyZr6KMZm2dxWM/PUa+NZ/a/j2pb3iakO2r+dD0GcF6MwX+VfEbOJ06jW/19lCFEEII4QP2n9tP0uYkZm+bzdm8s87tPRv2JCEugbuuuws/g1wq7g7Wa2S+akHOclPz9WplB84dgnkPQcp29Xbnp+HWl8EgvQaE8HUSfHUz75Qd0DJfvRB8Le5lFKJc0coOZBfYsNkdzveQO2k1X4ub+ap9hqTsgCitPGseTyx5ghlbZ+Bvb0Ez0xgc56N4wvgp9/qtAsBe7yYCBk6HkBpeHq0QQgghyrMCWwHf7fmOaZunseroKuf2mlVqMrLdSEa1G0VsRKwXR1g5FNV8vXbmq6Io6HSe68VyOQVXari1Yz78+BRYciCoKtw9DRr38MIIhRDuIMFXN9Mukb7Sj4E7ODNfvVHztfDUo9R89S1hgSZ0OlAUyMy3Uq2K+zta5Zcw81X7DEnZAVEa+9L2MfDbQRxM0RFte4sARytqWU/wX//xNNadQEGHrtvzGLo+A3r5/hJCCCHE5e06s4uk5CS+2P4F6fnpAOh1em5vdDsJcQnc0eQOjHpZZnuKTVHXvldabwcUBjkdiloS8EqNuTzlksxXaz4sex42z1Jv1+sMA6ZDaIx3BiiEcAspzOlmWqBIC4h6gpYh6I2yA+Zr1bAR5ZJBryM0oLDua65nSg/kaTVfA4o3OdUuJbJI8FWU0Nc7vqHTf0dy9sQDRFveJMDRksHGVfwUoAZeqRKNbvgi6Pa8BF6FEEIIcYk8ax6zt86m84zOtPy0JR+s/4D0/HTqhNbhlZtf4e+n/mbxkMX0a9pPAq8eVpT5evk5XMAF2wss3l9HXNRw6+x+SOpeGHjVQddnYNgiCbyKCstutzN+/HhiY2MJDAykYcOGvPbaayhKUexKURQmTJhAzZo1CQwMpEePHhw4cOCi46SnpzN06FBCQ0MJDw9n1KhR5OTkePrplIj8MriZVp/Ssw231KCWNy7PlrIDvisiyMT5fKvHmm5pZQeKm/mqncCQsgOiuAqsBTz49X/4Y3cIocqLAIQbzMyO+po2GT+DAjS4Be5JgirVvTtYIYQQQpQ7W1O2krQ5iTk75nDefB4Ag85A3+v6khiXSM+GPTHIiVuvulbNV5NBh0Gvw+5QKLDZCcN79VMVRXE2qA47sAB+eQ6suRAcBfdMg4a3eG1sQnjC22+/zaeffsrs2bNp0aIFmzZtYsSIEYSFhfHkk08C8M477/Dhhx8ye/ZsYmNjGT9+PL169WL37t0EBAQAMHToUE6fPs2KFSuwWq2MGDGCxMRE5s6d682nd1USfHWzosxXT5Yd0DJfvRF8VR8zwMuXc4iSiwj24+9zeR5rulWahlsgwVdxbYqi8OXG7by6eD02y/X4Awa9g3+3sZOQ8gbGjIOg08MtL0GXcaCXTH0hhBBCqLLN2Xy982uSkpPYeGqjc3tseCwJcQk81PYhaobU9OIIxYVshQlzVyo7oNPpCDQZyDHbyLd4t+mW2eYgkAJeNc4mdGlhneDYrnDPdAiJ9urYhCiL7OxssrKynLf9/f3x97+0lOHatWvp168fd9xxBwD169fnq6++YsOGDYC6jpsyZQovv/wy/fr1A+Dzzz8nOjqahQsXMnjwYPbs2cOyZcvYuHEj7du3B+Cjjz6iT58+vPfee8TElM/McQm+upk3gq9GZ81XLzTcsmkFxCWY4Wu0pluZHgi+2h0KBfbCsgPFDb4apOyAuDqHQ2H57hRe+2kzJzN0QC0UzNzW0o/JsacJ/fVlsJshJAYGfgb1bvT2kIUQQghRDiiKwqZTm0hKTuKrnV+RY1EvXzXpTdzd7G4S4hK4NfZW9DpZ45Q3tmtkvoJ6VWaO2ea85N9bzKd28YPfeJroT6Lo9Ohufh66/lvKXgmf17x584tuT5w4kVdeeeWS/W688UamTZvG/v37adKkCdu2beOPP/5g8uTJABw5coSUlBR69ChqNhcWFkbHjh1Zt24dgwcPZt26dYSHhzsDrwA9evRAr9ezfv167r77bvc8yTKS4KubaVl6nm245b3GRNrZRG8XMhclFx5UWPPVA2UHsgtszv+WzFdRVnaHwtKdp/lw5QH2p+YAOhzkERqxha8H30/Ljf8HKxaoOze6De7+HwRX9eqYhRBCCOF9ufZcpm6eyoxtM9iastW5vUnVJoxuN5rhbYcTFRzlvQGKa7pWzVco6kdS4K3gq6LAli8JWfIMYfp8UpUIood/AbE3eWc8QrjY7t27qVWrlvP25bJeAZ5//nmysrJo2rQpBoMBu93OG2+8wdChQwFISUkBIDr64kzw6Oho599SUlKIirr4e9loNBIZGencpzyS4KubWQuzTz1adkDvnYZbiqI4a9xKzVffo2W+eqLswPkCNcAb5Gco9mdD20+Cr+JCDofCqNkb+X3fWfU2uWQZf+TBTrWY3GYQpu+GQfph0Bmgx0To9ISUGRBCCCEqMUVRWHdiHVM3TuWbnd9g2aHOff0N/gxsPpCEuAS61uuKTue5hsmi9KyFS96rZb4GFq5NvZL5as6BxWNhx7fogdX2Vow3PMkqCbyKCiQkJITQ0NBr7vftt98yZ84c5s6dS4sWLdi6dStPP/00MTExDB8+3AMj9R4JvrqZFoz0RtkBT2e+mi8IimlnF4XviCjMfM3M9UDma76a+RoSUPyvIC173BsZ3aL8+nrjcX7fdxYFC+eN89AF/c6suz+hf3YazOwNdguE1YGBM6BOB28PVwghhBBekp6fzhfbvmBa8jR2n93t3N68WnMS4xN5sM2DRAZGenGEojSKMl+vEnz1U4OvHs98TdkB8x6CcwdBZyC1/b8YvqY11QMCPTsOIcqJZ555hueff57BgwcD0KpVK44ePcpbb73F8OHDqVGjBgCpqanUrFlUWzs1NZW2bdsCUKNGDc6cOXPRcW02G+np6c77l0cSfHUzLVB0tTNxrlYUfFVQFMVjZ20v/DGTzFffE+6FzNewgOJ3G3WWHZDgqyh0KjOXiT9uAYxkmGbTuM5xFty1lPqr3oM9i9SdrusD/T6BIFlMCSGEEJWNoiisPrqaacnTWLB7AWa7GYBAYyCDmg+ieX5zxg4ci5+fn5dHKkrD4VCwK+pa96o1X41a8NVD6whFgc0zYenzF/QbmMEJrkNZs84ZDBaissnLy0P/j6sQDQYDjsJm8bGxsdSoUYOVK1c6g61ZWVmsX7+eRx99FIBOnTqRmZnJ5s2biY+PB+DXX3/F4XDQsWNHzz2ZEpLgq5sVNdzy3GUrpgvezHaH4gzGupt2GYdRr/Nopq9wjaKGW+7PfM3KVx8jNLD4X0HuKjtQYLWz61QWbeuEY9DL5WW+4nT2aXp88jVWWxPMuv0M7RjDlNbP4f/1g5B5FPQmuG0S3PAoyGWDQgghRKVyJvcMs7fOZvqW6ew/t9+5vW2NtiTGJTKk1RCCDEEsWbJEygv4sAuviLta5mtAYbBT60/iVgVZ8ONTsOs79XbjXtD/UwiuSv6BNKCoDIIQlU3fvn154403qFu3Li1atGDLli1MnjyZkSNHAqDT6Xj66ad5/fXXady4MbGxsYwfP56YmBj69+8PQLNmzejduzcJCQlMnToVq9XKmDFjGDx4MDExMV58dlcnwVc30wJFnsx8NV3wWDaHgqd6X2lnEiXr1TdFOBtuuT/zNauw4VZoSTJfC4OvZhcHX6f8coCpqw4x+d423BNX26XHFu7x25HfGDr3bfyyn0DBzjO3xzDO5A+z+oLDCuH1YNBMqBXv7aEKIYQQwkMcioOVh1eSlJzEwr0LsTrUk/1V/Kpwf8v7SYxPJL5mvDPYarW6P+FAuNeF64Kr13xV/+b2mq+ntqplBjKOgN4I3SdCpzHOfgPa48t6WVRWH330EePHj+exxx7jzJkzxMTE8PDDDzNhwgTnPs8++yy5ubkkJiaSmZlJly5dWLZsGQEBAc595syZw5gxY+jevTt6vZ4BAwbw4YcfeuMpFZukJ7qZs+yAJ2u+XpC958n6mAXOHxN5W/miorID7p+Ini/MfA0rQearn5tqvh5IzQZgX0q2S48rXM+hOHhj9Rvc9nlf9Nn3A/BQnB/jTi6En19QA6/N7oKHV0vgVYh/sNvtjB8/ntjYWAIDA2nYsCGvvfYailLUnFNRFCZMmEDNmjUJDAykR48eHDhw4KLjpKenM3ToUEJDQwkPD2fUqFHk5ORctM/27du56aabCAgIoE6dOrzzzjseeY5CiMrpdPZp3lzzJo0+bETPL3syb/c8rA4r18dcT1LfJE6NO8W0vtNoH9NeslwrmAvLkV1tva0FO91W81VRYP00+Ow2NfAaVgdGLIPOT17U6FXWy6KyCwkJYcqUKRw9epT8/HwOHTrE66+/flHpF51Ox6RJk0hJSaGgoIBffvmFJk2aXHScyMhI5s6dS3Z2NufPn2fGjBlUqVLF00+nRCTz1c0sdnVR48nL8C98LKtducqerlUgZ/J8WkRwYcOtPIvbawVnFTbcCg0sRc1XF2e+puWqmb5nss0uPa5wrbS8NB747gF+PvQzkZZHMFKN3mFHeeXEJ5B1Agx+0OtNuH60lBkQ4jLefvttPv30U2bPnk2LFi3YtGkTI0aMICwsjCeffBKAd955hw8//JDZs2c7L/Pq1asXu3fvdmYbDB06lNOnT7NixQqsVisjRowgMTGRuXPnAmpdrp49e9KjRw+mTp3Kjh07GDlyJOHh4SQmJnrt+QshKha7w87Ph34mKTmJH/f9iF1R1yFh/mE80PoBEuISaFOjjZdHKdzNfMFVpldbuwS6M/ianwmLxsCeH9Xb190B/T6+bL8BLfNVyg4IUflI8NXNLDb1C9aTZQcMeh06nXoCzubBzFe5jMK3aTVfbQ6FbLOtRCUBSiqrNA233FTz9VyOGnQ9k13g0uMK11l7fC33zb+PE1knCNG1IdR+OwmGH3neMg+d2QYRsTBoFsS09fZQhSi31q5dS79+/bjjjjsAqF+/Pl999RUbNmwA1KzXKVOm8PLLL9OvXz8APv/8c6Kjo1m4cCGDBw9mz549LFu2jI0bN9K+fXtAvXysT58+vPfee8TExDBnzhwsFgszZszAz8+PFi1asHXrViZPnizBVyFEmR0/f5wZW2bw2ZbPOJ513Lm9c53OJMQlMKjFIIJMQV4cofAkbV1wtXqvULQ+dXnZgRObYf5DkHlM7TfQ8zXo+MgVEwG04K803BKi8pF8dzezeiHzFYqablkdnst8NTtrvsrbyhcFmAzOs7CZue4tPaBlvoaUg7ID53IKM1+zJPO1vFEUhffXvs/Ns27mRNYJmkQ2p6v/y3xmep8XTV+hV2zQ4h61zIAEXkUllZ2dTVZWlvN/ZvPlv8tuvPFGVq5cyf79auOZbdu28ccff3D77bcDcOTIEVJSUujRo4fzPmFhYXTs2JF169YBsG7dOsLDw52BV4AePXqg1+tZv369c5+uXbtedPlYr1692LdvHxkZGa598kKISsHmsPHD3h+4c+6d1P+gPq+seoXjWceJDIzk6Y5Ps/PRnfwx8g+Gtx0ugddKxpn5eo21dlHZARetIxQF1n0CM3qpgdfwejDq52s2etUafkmykhCVj2S+upmz5qvRs5fBmgw6LHbPZr46yw54qsOXcLmIIBP55+1k5FmoW9V9k9fzZcl8deF7Os9ic54Bl7ID5UtGfgYjfhjBD/t+AGBwy8H0ddzBLTufoaYhHcXgj+72tyH+ISkzICq15s2bX3R74sSJvPLKK5fs9/zzz5OVlUXTpk0xGAzY7XbeeOMNhg4dCkBKSgoA0dHRF90vOjra+beUlBSioqIu+rvRaCQyMvKifWJjYy85hva3iIiIUj5TIURlcyTjCNOTpzNz60xO55x2bu9WvxsJcQnc0+weAowBVzmCqOiKm/ka6MrM17x0WPgY7F+q3m7eD+76CALCrnlXuVJUiMpLgq9uZnGejfPsF6zRoAfsnq35apPLKHxdeJAfp84XkJFncevjZBU23AotQearqXBSZXZh2QEt6xXUJmAFVrtMhsqBzac2M2jeII5kHsHP4MeUnpMZlHae8PVPYNQ5yK4SS8gDX0KNlt4eqhBet3v3bmrVquW87e/vf9n9vv32W+bMmcPcuXOdpQCefvppYmJiGD58uKeGK4QQV2WxW1i0bxHTNk9jxeEVzu3Vg6rzUNuHGB03miZVm1zlCKIyubDm69UE+ql/L7CUMfh6bD3MH1nqfgNa5q3UfBWi8pHgq5tpWXomg+czX8H1l2hfTb5FO/MoPya+qqjplpvLDhQUNtwqRearK08opOVcnO16NttMnUi5XM1bFEXh002fMvbnsVjsFmLDY/n+zmm0/vNjdId/Ax2sDe5Opydmg3+It4crRLkQEhJCaGjoNfd75plneP755xk8eDAArVq14ujRo7z11lsMHz6cGjVqAJCamkrNmjWd90tNTaVt27YA1KhRgzNnzlx0XJvNRnp6uvP+NWrUIDU19aJ9tNvaPmWRn5+PoigEBanf1UePHuX777+nefPm9OzZs8zHF0J4x/5z+5mePJ1ZW2dxNu+sc/ttDW4jIS6Bfk374Wfwu8oRRGWkrbWLW/NVSxYqMYcD1n4IKyeBYofIBmq/gZola+pWIA23hPAJ7phvSnFON9OCnyYPNtwCMBbWfLV5MvPVeRmFvK18VXhh0y13Z76eL8x8DStFzVdLaSdNl3Fh5itI0y1vyjZnc/+C+3l8yeNY7Bb6N+3P9t4f0+b7x9Ad/o18xY+XHI9Qb/SX6CTwKkSJ5eXloddf/PtsMBhwONR5SmxsLDVq1GDlypXOv2dlZbF+/Xo6deoEQKdOncjMzGTz5s3OfX799VccDgcdO3Z07rN69Wqs1qKTeCtWrOC6665zScmBfv368fnnnwOQmZlJx44def/99+nXrx+ffvppmY8vhPCcAlsBc3fM5ZbZt3Ddx9fx7tp3OZt3lppVavJilxc59OQhlj+4nEEtBkngVVxWcTNfnQ23SpP5mpsGc++FXyaqgdeWA9V+AyUMvF74+HKlqBDlmzvmmxIlczNLMYuAu5pRy3x1eLDmq01q2Pi6iCA1EzXDjZmviqIUZb4GlqLmqyvLDuRenPkqTbe8Y3vqdtonteebXd9g1Bv5v9ve47uoDlT5eijkpHJQqc1dltdp2PMRakVIZrIQpdG3b1/eeOMNfvrpJ/7++2++//57Jk+ezN133w2ATqfj6aef5vXXX2fRokXs2LGDYcOGERMTQ//+/QFo1qwZvXv3JiEhgQ0bNvDnn38yZswYBg8eTExMDABDhgzBz8+PUaNGsWvXLr755hs++OADxo0b55LnkZyczE033QTA/PnziY6O5ujRo3z++ed8+OGHLnkMIYR77T67m7HLxlJrci2GfjeU3//+Hb1OT5/GfVh430KOjT3GG93foEFEA28PVZRzbq/5enQtTO0CB1eAMQD6fgADppf6Ciyp+SqEb3DHfFPKDriZdon0tc7GuZoWqPJs5qvUsPF1EYWZr5luzHzNs9ixO9T3ZWhAKTJfXVhKI+2SzFcJvnrazC0zeWzJYxTYCqgdWpvv+nzK9X/9D46sBuCPkN6MPnsf19WJZviN9b07WCF82EcffcT48eN57LHHOHPmDDExMTz88MNMmDDBuc+zzz5Lbm4uiYmJZGZm0qVLF5YtW0ZAQFFDmzlz5jBmzBi6d++OXq9nwIABF01Cw8LCWL58OY8//jjx8fFUq1aNCRMmkJiY6JLnkZeXR0iIuuhdvnw599xzD3q9nhtuuIGjR4+65DGEEK6XZ81j3q55TEuextrja53b64TWYVS7UYxsN5I6YXW8OELhi8zFTHRyZr5ai7mOcDjgj/fhtzdBcUDVxmqZgTL2G8iXK0WF8AnumG9K8NXNtLNxJi9lvto8WPNVyg74vqKyA+7LfNVKDhh0SokC9Vrw1Wpz3QkFKTvgPbmWXB5f8jizt80GoHej3nzd7mHCFj0NuWfBFMz2thN4YE0djHod/7mnFQa9Z2tnC1GRhISEMGXKFKZMmXLFfXQ6HZMmTWLSpElX3CcyMpK5c+de9bFat27NmjVrSjvUq2rUqBELFy7k7rvv5ueff2bs2LEAnDlzpli1b4UQnrUtZRvTNk9jzo45nDefB8CgM9D3ur4kxCXQq2EvDHpJ3BClYyluw63CNYe5OJmvOWfgu0Q4/Jt6u/VguON98K9SprGC1HwVwle4Y74pwVc307L0PJ35qtV8dWWW4LUUyGUUPk8rO+DOzFct+BpoVBf6xaWd0Ta78D2tlR0IDzKRmWeVsgMesufsHgbNG8Sus7vQ6/S8cfMknrPZ0X37EKBAVAty+k1n9KxTgJnErg1oVlOCKkIImDBhAkOGDGHs2LF0797dWY92+fLltGvXzsujE0KAWsf9651fk5ScxMZTG53bY8NjGR03mofaPkRMSIwXRygqCq0XxDWDr37q369ZduDwKvguAXJSwRioBl3bDXXJWEGCr0L4CnfMNyX46kaKohQ13DJ4NmPL5Mx89UbDLfkx8VURHmi4lVUYfA0q4dvEZHRDzdfCzNdmNUJZd/iclB3wgLk75pL4YyK51lxqVKnBd70/otP6z+BY4SWI8SOg91u8tfggZ7LNxFYL5snujb07aCFEuTFw4EC6dOnC6dOnadOmqNlJ9+7dnfVrhRCepygKm09vZtrmaXy18ytyLDkAmPQm+jftT0JcAt0bdEevkyvkhOtYCte616r56m+8RsMthx1WvQOr3gYUqN5MLTMQ1dSFo72g7IA03BKiXHPHfFOCr25kcygohbFPzzfcKqz56smGW4U1dCT46rvCtYZbue4vOxBYwm8f7TNkdWnNVzXY2jxGgq/uVmArYOyysUzdPBWAW+rfwvx2DxO5+BnITwe/EOg7BVoNZOPf6cxZfwyAN+9uJd8pQginX3/9lRtvvJEaNWpctL1Dhw5eGpEQldv5gvPM2TGHpOQktqZsdW5vHNmYhLgEhrcdTlRwlPcGKCo0rYzAtTNf1blkweUyX7NTYMFo+LuwXE67B+H2d8DP9U1eteCvZL4KUb65Y74pwVc3ujBI5OmyA1rmq9WDma9SQNz3eSLzVQu+BhlL9t70c0fma25h5mvhJe1nsqTmqzscSj/EoHmD2JKyBR06JnR5gQl2PfrvChvw1GitZhdUbYjZZuf5BdsBuK99HTo1rOq9gQshyp277roLm83G9ddfT7du3bj55pvp3LkzgYGB3h6aEJWGoiisO7GOpOQkvtn5Dfm2fAD8Df4MbD6QhLgEutbrWqLyUkKUhlZi71qZr1qws+CfDbcOrlTru+algSlYTQRofa87hnrR40tigRDlmzvmmxJ8daMLGwN5uuGWySuZr4XBV6P8mPiqiGA1+JpnsWO22Z2X6LhSVoENgMASHlrLfHVV8NXhUEh3Bl/VTobnci1Y7Q6Pf14rsu/2fMeIH0aQZc6iWlA15vecws0bZ8GJDeoO1ydAz9fBpHZT/+9vhzh0NpdqVfx5sU8z7w1cCFEuZWRksGHDBlatWsWqVauYMmUKFouF9u3bc8stt/D66697e4hCVFjp+el8se0LkpKT2HV2l3N78+rNSYxL5ME2DxIZGOnFEYrKxqw13LrG3F0LdlrsDuwOBYNih9/fhDWTAQWiW6qJANXcW+pKar4K4RvcMd+U4Ksbme3ql6tOB0YPd+nWHs+VneGvxSxn8nxeaIARg16H3aGQmWclOtT1r2Wpyw4YXdtE7ny+FbtD/Xw0iqqCUa/D5lBIyzFTM0wyqMrKYrfw7Ipn+WD9BwB0rtOZhe0Sqbb0RSjIBP8w6PcRNO/nvM+B1Gz++/tBAF65qzlhhWUwhBBCYzKZ6Ny5M507d+bFF19k165dvPvuu8yZM4e//vpLgq9CuJiiKKw+upqk5CTm756P2a6WaAo0BnJvi3tJjE+kU+1OkuUqvEJLyrhWwsiFwU7zuWME/fhIUb+B9iOh15tgcv/8P1+Cr0L4BHfMNyX46kbaJf8mg97jExKt5qvVk5mvhd0mtW6SwvfodDrCA02cy7WQkWchOjTA5Y/hbLhVyuCr1UWZr+dy1cVDWKAJf6OBalX8Sckq4EyWBF/L6tj5Y9w7717Wn1wPwHMdx/KGYsLwwxPqDjFxMHAGRMY672O22Xlm/nasdoXuTaO4o1VNbwxdCFHO7d+/n99//53ff/+dVatWYTabuemmm3jvvffo1q2bt4cnRIVxNvcss7fNJik5if3n9ju3t63RloS4BIa0GkJ4QLj3BigEF2S+Gq++1tbKEnTTbyFgxpiifgN3fQAtB7h9nKCeyChquCXrZSHKM3fMNyX46kbWYl4G4Q5azVebJ2u+WqTsQEUQHlQYfHVT062y1nw1uyjzNS1HLTlQtYpaaiEqtDD4Kk23yuSn/T8xbOEw0vPTCQ8I59vu73LblrlwcrO6ww2PQY9XwejnvI/DofDvedvZejyTEH8jr/VvKRk0QojLatq0KdWrV+epp57i+eefp1WrVvJ9IYSLOBQHvx75lWmbp7Fw70KsDnXOVsWvCve3vJ/E+ETia8bLZ06UG0U1X6++/tQrNl72+4rR+h8hH6jZBgbOhKoNPTBKldnmcDbjlsxXIco3d8w3JfjqRtqPgaebbUFRzVdXdoa/Fi3z1V9+THya2nQrl0w3Nd3SMl9LWvNVO6FgsTlQFKXMX37nCoOv1YL9AYgKUf//THbFa7pldyh89sdhAkwGbmxYjYbVg12+cLI5bIz/dTz/+fM/ALSPac/itg8TvWISmM9DQDj0/xSa9rnkvm//vJcft53CqNcx9cF4YsIl81gIcXlPPvkkq1evZtKkSSxevJhu3brRrVs3unTpQlCQ6ztTC1EZnM4+zcytM/lsy2cczjjs3H59zPUkxCUwuOVgQvxDvDhCIS5PK3t31fV25nGYP5LRerXfQGarEYT3exuM/p4YopP5gmZfUqZPiPLNHfNNCb66kVaDRgsaeZJRrzXc8lzma1H3RrmMwpeFB6kZiRl57s18LWnNV39D0STF5lDK/LnSyg5oma/VQ9QSC2eyKl7m68ItJ3lzyV7n7ehQfzo3rMaNjarRuVHVMpdZOJV9ivsX3M/qo6sBeDr+Ud4jAMNP/1J3qH29WmYgvO4l9/1i3d/8b5W60Ht7QGs6N6pWprEIISq2KVOmAJCZmcmaNWtYtWoVL730Ert27aJdu3b8+eef3h2gED7C7rDz86GfSUpO4sd9P2JX1CSKUP9QHmj1AAnxCbSt0da7gxTiGq6Z7LR3CSx8FAoyySaIf1sSGdNxHOEeDrxCUb1Xo14nzX2FKOfcMd+U4KsbaT8G3vhy1QJTrqqPWRzSvbFiiChscpThpszX82Ws+QrqiY2yfq4uKTvgzHyteMHXRdtOAVA3MoiUrAJSs8x8t+Uk3205CUCDasHc2KgqnRtW44YGVYkI9rva4S6y8vBKhnw3hDO5ZwjxC+HrW9+kz9Zv4fQ2dYfOT8Gt48FwafOsX3anMnGR2i35X7c1YUB87TI+UyFEZWG327FarZjNZgoKCjCbzezbt8/bwxKi3Dt+/jgztszgsy2fcTzruHP7jXVuJDEukUEtBhFkkixy4RvMVyrzZ7PALxPhr/+qt2PieDjzEdYWVGFU4ZrV06TZlhC+x5XzTQm+upGz5qsXyg4YteCrRzNfC2u+yg+KT9MCb24rO1CglR0o2XvzwkxXi81BcBlPWJ/LKcx8LTyQ1lzsbAUrO5Cea+GPg2kAzB7ZgZphAWw+msGfB9P489A5dpzI5HBaLofTcvnyr2PodNC8ZiidG1XjxoZVuaFB1ct+pu2KndfXvM5ra15DQaF1dGuWtkkgZuV/wJINgZFw9/+gSc/Ljmvb8Uye+GoLDgXua1+HMbc2cuu/gxCiYnjyySf5/fff2b17NxEREXTt2pWEhAS6detGq1atvD08Icolm8PGT/t/Iik5iaUHl+JQ1DVKREAEw9oMIyEugRZRLbw8SiFKTltv+1+43s74G+aNgFPJ6u1OY6D7RDI+WQ9kOdesnubsj+Ina2Uhyjt3zDcl+OpG1sJmV95ouOUsO+Chmq92h+J8vhJ89W3hzsxXdzfcKtn9jAY9eh04lKKs8rJw1nz9R+ZragUrO7B052nsDoVWtcKIrRYMQOdG1ZyX95/Pt7L+8DnWHjrHnwfTOHAmh12nsth1Kotpqw9TKzyQT4bG0bZOuPOYZ3LPMOnwJLZlq9mtj7Z5iA91VTD+/JK6Q91OMOAzCKt12TEdT89j1OyN5FvtdG1SndfvlgZbQojiOX36NImJiXTr1o2WLVt6ezhClGtHMo7w2ZbPmLFlBqdzTju3d6vfjYS4BO5pdg8BxgAvjlCIsjH/M9lp9yL4YUxRv4G7p8J1twMQWFgaL9/Lma9Sok+I8s8d802vf/I/+eQT6tevT0BAAB07dmTDhg1X3T8zM5PHH3+cmjVr4u/vT5MmTViyZImHRlsyFrv6BeuNsgPaD5Cnar5eeAZRflB8W0SQ+zJfzTa7szZwSWu+QtH72uKCchpFNV8LG26FVsyGW4u2qiUH+rapedm/hwWa6NmiBq/c1YIV425mw4vdmXJfWwbF16ZaFX9OZuYzaOpaZv15BEVR+OPYH3T4rAPbsrcRZAri++7v8N/T+zFu+RzQwU3/guGLrxh4zcyzMHzmBtJyLDSvGcp/h8ZJ3SshRLHNmzePMWPGuCXwWpHnpKLysNgtzN89n55f9KThhw15Y80bnM45TfWg6jxz4zPsG7OP34b/xpBWQyTwKnyelpARqLPCkmfg2wfVwGvtDvDIH87AK0BgYcaptzJfzVJ2QAif4Y75plczX7/55hvGjRvH1KlT6dixI1OmTKFXr17s27ePqKioS/a3WCzcdtttREVFMX/+fGrVqsXRo0cJDw/3/OCLwWIrzHz1RtkBfWHZAQ9lvl4UfDXKD4ov02q+pue6PvialW8DQKeDgFK8TfwMegqsDpdmvlYN1jJf1QVIWo4Fu0PBoPf9TMyU8wVs+DsdgDtaxxTrPlGhAfRvV4v+7WqRVWDlufnbWbozhVd+3M0Xm/5idebD2Mimtn9t/uj0BPVW/R9YcyGoGtwzDRp1v+KxC6x2Ej7fxOGzucSEBTBzxPVU8ZcLMIQQJfPFF18wdepUjhw5wrp166hXrx5TpkwhNjaWfv36leqYFX1OKiq+A+cOkJScxKytszibd9a5/bYGt5EQl0C/pv3wMxS/prsQvsBsdVBPl0LH31+HjN3qxiv0G9DWqF4rOyDBVyF8iqvnm15NN5o8eTIJCQmMGDGC5s2bM3XqVIKCgpgxY8Zl958xYwbp6eksXLiQzp07U79+fW6++WbatGnj4ZEXj9XZcMvzQRxjYSaZp4Kv2o+Jn1GPvgIErSqzosxX15cd0EoOhPgbKc3bxJWZr2k5F2e+Vqvih06nltBwR+DZG37acRpFgevrR1ArPLDE9w8NMPHfoXE807s+Op2dQ6dDiSp4n4H1ElkV2Ip6v72hBl7r3wSP/nnVwKvDofCvedvY+HcGIQFGZo3s4KyzK4QQxfXpp58ybtw4+vTpQ2ZmJvbCq4zCw8OdnWlLo6LPSUXFVGArYO6Oudwy+xaafNyEd9e+y9m8s9SoUoMXu7zIoScPsfzB5QxqMUgCr6JC6mJexWK/lwjJ2A1BVWHofLht0mUbvWq1VrXaq56WL/1RhPAZ7phvei3lyGKxsHnzZl544QXnNr1eT48ePVi3bt1l77No0SI6derE448/zg8//ED16tUZMmQIzz33HAbD5b/EzGYzZnNRDcfs7GwArFYrVqt7alpq8s3q8Y16ndsf65/0qFm3FqvdI4+dk68GqwKMerc/nnZ8T/+bVhYhfmqAMyPP4vJ/4/TsfABCA9SvnpIeX7s8Pd9ctrFZbA6yCtQs3DD/ovdsZJAf53ItnMrIITzA9y+FX7T1JAB9WkaX+t9r06lNvLv1fk77+RNleYFmOHjjyB800J1AQYfjpn/j6PJv0BvgKo/x9s/7+Wn7aUwGHZ/c34bYyAD5DHuRr32PWq1WFMWOw3HtBZOi2J2/8b5yv9LwldfO1T766COSkpLo378///nPf5zb27dvz7///e9SHbMyzEmF63nze3T32d3M2DqDL3d+SXq+eoWLDh29G/ZmZNuR9GnUB1Nh8EneW1fma7+F4gLWfPQrXmKC+XPQQVb19gQOngmhNa84H/UvTIjKKfDOd64n18u+RD6HV1aSeSV4Zy5rs1XMxDt3zDe9FnxNS0vDbrcTHR190fbo6Gj27t172fscPnyYX3/9laFDh7JkyRIOHjzIY489htVqZeLEiZe9z1tvvcWrr756yfbVq1eze/fusj+Rq0hO1QEGMs+d9XgNsEMn1cf++9hxliw56vbHO5ELYAS71WPPdcWKFR55nMomywJgJDPPwuKflpQqQ/VKdmeo70usahC2pK+h1WwAdKxa8yfHQ0s/jkwzgBG9TuGP31Y4n2OAoh5/ya9/8neEZ+olu0taAWw7YUSHgvH0TpYs2Vmi+yuKwpK0Jcw8NRObYqNGQA0+jfqdHmd/IgALZ5Rw/hv4KM3PN8N/2c9XPdaaFB3zj6jBiPtibWTsXc+Sy3/NCw/zle/R7OxsDp3UExAccs19C3KzWVFwiJCQEJ+5X2mkpaWV6n6+7siRI7Rr1+6S7f7+/uTm5pbqmJVhTircx1Pfo2aHmT8z/2TFuRXsyd3j3F7VVJUekT3oUbUH1f2qwyFYccg3vtvLC1/5LRSqKgWnaX/kY8IKjuNQdHxs74dfeD9q/rEF2HLF+6We0gN6du7Zx5KcPVfcz102p6jroIxzZ6Q++GXI5/BSJZlXgnfmsutOVcz5qDvmmz5VbM/hcBAVFcW0adMwGAzEx8dz8uRJ3n333StOdF944QXGjRvnvH3y5EmaN29O165dqV+/vlvHm7H+GBzeS62aNejTp61bH+ufUtce5cdj+4iuGUOfPq3d/njJxzJh+wbCQ4Lo0+cmtz6W1WplxYoV3HbbbZhMl15SIsrGYnMwfvMvKOjocstthAe57t/Ytu007N1BreoRQFqJX8OPDv5JWkEu8R060qlB1VKPY9epLEj+i2pVArjzjpud2xekbebkgXPUa9qaPvGXbxjlK6auOgwcpFPDqgzu375E980yZ/HwTw+z4OQCAO5v3JcZxkgCdn8PwLHwDgxMeYgz5nAaHgnmo/va0Di6ymWPtXLPGb77aysA43o04tGbG5T6OQnX8bXv0fT0dI6sOUxQSPg1983LzuS2mxoQGRnpM/crjb///rtU9/N1sbGxbN26lXr16l20fdmyZTRr1sxj4/C1OalwPU99j25L3caMrTOYu2cu583nATDoDPRp3IfRbUfTs0FPDHq5jLk0fO23UIBux7cYlk5CZ81FCa7OwzmJrLC1YEnXjjSuEXbV+25fto8/U49Su34D+vRq4qERFzn9599wZD+xdWrRp08rjz9+eSWfwysrybwSvDOX7VSvcbHG5mvcMd/0WvC1WrVqGAwGUlNTL9qemppKjRo1LnufmjVrYjKZLrqcq1mzZqSkpGCxWPDzu7SWkb+/P/7+/s7bWVlZAJhMJrd/uG2Kmk4X4Gf0+BeJv0l9aR2KziOPbXWozzXQ5Lnn6onXsDIymaCKv5Ecs40cq0J1F/4b51rVWq3hhXVlS/oa+hfWSHKgL9Nrf96sjqNqFf+LjhMdqtZFTc+z+vx766ed6ndrv7a1SvRctqVsY9C8QRxIP4BJb2LmDf9iyL5f0KWtAp0ebnmRmjc8yeBvlvHNMX8Onc1lwP/W83r/lgyIr33RsbYez+TpedtxKHB/hzo80b0JOl3FvDTFV/nK96jJZEKnM6AvRoBBpzM4n5ev3K80fOF1c4dx48bx+OOPU1BQgKIobNiwga+++oq33nqL6dOnl+qYlWFOKtzHHa9fjiWHr3d+TVJyEhtObnBujw2PZXTcaB5q+xAxIcVrpCmuTT6DPsCSB0uega1fqrfr34RuwHRWvb0FcBAc4HfN1zDYX/27xa545fXWSs0G+cv77XLkc3ipkswrwTtzWaPRp/I5i80d802v/Uv5+fkRHx/PypUr6d+/P6BmEaxcuZIxY8Zc9j6dO3dm7ty5OBwO9Hq1HuP+/fupWbPmZSe53ma1q5cta3UqPclYWNPGFV3hi6PAWUDc9+tkCggPMpFjtpGRZyGWYJcd93xhE6+wwNL9sLqq4da5wmZb1apc/L2hNYA6k22+5D6+5EBqNntTsjEZdPRuUbNY91EUhc+2fMYTS5+gwFZA3dA6/NbqIRr89T+wFUBITRjwGdTvDFYrDUPhh8du4JnvdrHmQBr/mreNDUfSebVfCwJMBo6dy2PUrI0UWB3c3KQ6r/VrKYFXIUSZjR49msDAQF5++WXy8vIYMmQIMTExfPDBBwwePLhUx6wMc1JR/imKwubTm0nanMTcnXPJseQAYNKb6N+0PwlxCXRv0B29TubaopI5swfmPQRn9wI66PY8dH0GRad3rgm0NcLVaEkc2rrV07SGW4HScEuIcs8d802vhqnHjRvH8OHDad++PR06dGDKlCnk5uYyYsQIAIYNG0atWrV46623AHj00Uf5+OOPeeqpp3jiiSc4cOAAb775Jk8++aQ3n8YVWQsDn94IvpoKFwI2TwVfbeqPib/8mFQIEUF+nMjIJzPP4tLjZhWowdeQACOU4q3pV/hZKutJhXM56vOqGnzxAjkqVM1ISs0qKNPxve3HbacAuLlJdcKKUTYi15LLoz89yhfbvwBgYINefGmqiv8fH6g7NLoN7p4KwdUuul/VKv7MGtGBT347yP/9sp9vNh1n24lM3ri7Fc/M28a5XAstYkL5ZGgcRi98DwohKqahQ4cydOhQ8vLyyMnJISoqqszHrOhzUlF+nS84z9wdc0lKTmJLSlG9ysaRjUmIS2B42+FEBZf9PS6Ez1EU2DoHfvo32PKhSjQMmA6xXQGw2IqCqP7FCL5qQc98q2fWx/+UX5j6Gugnc2IhfIGr55teDb7ed999nD17lgkTJpCSkkLbtm1ZtmyZs+HBsWPHnNkEAHXq1OHnn39m7NixtG7dmlq1avHUU0/x3HPPeespXJV2Jq44PwaupmW+2hyeaRpUUPgjJmfyKgatzmtGrmu7Tp7PvyDztRR1ql2V+ZqWq2a2Vq3if9H2qBD1ti9nviqKwo/bTwPQt821L0ncc3YPA+cNZPfZ3Rh0BpLaP8FDB39Hl74OdAboPgFufBL0l/8eM+h1PNm9MfH1Injq6y3sTclmwKdrAagVHsjMh66nin/FvBxFCOFdQUFBBAUFueRYFX1OKsoXRVH468RfJCUn8c2ub8iz5gHgb/BnQPMBJMQlcHO9m+WKEVF5mXPgp3/B9q/V2w1vhbunQZXqRbtcsB7wK8ZJ/kC/wuCrxTuZr+bCYHGAUdbLQvgSV803vb4iHjNmzBUv6fr9998v2dapUyf++usvN4/KNYoyXz0/cdKyba0eynzNl7IDFUpEYU3WDBdnvmrB19DSBl9d9L52Zr7+o+xA9ZDCsgNZvht83XUqiyNpuQSY9PRoFn3Vfedsn0Pi4kTyrHnUDK7BqpbDaLxxBtgtEFobBs6Auh2L9bidG1Xjpydv4omvtrDhSDohAUZmjbieqMJSDkIIUVpxcXGsXLmSiIgI2rVrd9WAVHJycqkfpyLPSUX5kJ6fzpfbv2Ta5mnsOrvLub159eYkxiXyQOsHqBpU+oaiQlQIKTvVMgPnDhT2G3gJuoy7JBHgwmSM4pQd0NapZpuXyg44M18l+CpEeeTu+abXg68VmXY2zitlB7TMV7tnMl/NzuCr/JhUBBGFma+Zea7NfM3KtwEQGlC6rx6X13wNvnzm69lsM4qi+GTGiVZyoHuzaIKvkHFaYCvgqaVPMS15GgB31buZb/yiCfhrqrpDk9uh/38hqGRd2KNDA5g7uiM/7ThNy1phNKxepfRPRAghCvXr18/ZqKpfv34++d0sKi9FUVhzbA1JyUnM2zUPs12dgwQaA7mv5X0kxCXQqXYneV8LoSiweRYsfQ7sZgiJgYGfQb0bL7u7ttY26Io3Z3eWHfBS5mu+rJeFKNfcPd+U4Ksbadl5xTkT52pGvWczX50Nt+Qyigoh3M2Zr2GBJnJKcX/tRIa5rMHX3Ctlvqpftha7g/P5Vue/g69wOBRn8LVv68uXHDiYfpBB8waxNWUrOnRMbZdIwuG16DK3gN4Et70KNzwGpfyxMRr09Gtbq9TPQQgh/mnixInO/37llVe8NxAhSiAtL43ZW2eTlJzEvnP7nNvbRLchMT6RIa2GEB4Q7r0BClGeFGTB4qdh5wL1duOe0H8qBF85E1xLxijuhZcBzpqv3gq+Spk+Icozd883JfjqRt5suKXVfLV6KPPVWfNVLqOoELTMV7eVHQgwlir4qp3IKOv7uqjswMWZrwEmA2GBJs7nWzmTbfa54GvysQxOnS+gir+RbtdVv+TvC3YvYOSikWSZs6geWI3VzYfSNPlLcFghvC4MnAW14z0/cCGEKKbRo0fzwAMP0K1bN28PRYhLOBQHvx35jaTkJL7f+z0WuzrfCDYFM6TVEBLiEmgf016yXIW40OltapmB9MOgN6r9Bjo9ccV+AxqtfICxmB8nbwdfCyyS+SqEr3DHfFOCr26knY0rTgFwV9MCvjaHZ2u++kvN1wohIrgw89XFDbeyCrTgq4lTpbi/K8oOKIpCWmHZgarBlwZXo0L81eBrlpkm0SGlfpzLsdodbD9xnja1wzC64XtBy3rt2SL6oomdxW7h2RXP8sH6DwC4vdYNLPCvQeCmmeoOzfrCXR9DYLjLxySEEK509uxZevfuTfXq1Rk8eDAPPPAAbdq08fawRCWXkpPCrK2zmJ48nUMZh5zbr4+5noS4BAa3HEyIv2vnFEL4PEWBjdPh5xfVfgNhddR+A3U6FOvu2nqguBeZahmnZqtn1sf/VGDTar7KelmI8s4d800JvrqRlp3njbIDzuCrxzJfpexAReKOhlt2h0J2gVrzNSywlDVfC9/XFnvpz1jnWuzOsgX/LDsAEBXqz4EzOZzJLij1Y1zJF+uOMmnxbnq1iObTofHo9a7LfLHZHfy04zQAfdsUlRw4mnmUe+ffy4aTGwD4uNVwHju6Ed2J3WDwg55vQIeEUpcZEEIIT/rhhx/IyMhg3rx5zJ07l8mTJ9O0aVOGDh3KkCFDqF+/vreHKCoJu8NOclYysxbMYvGBxdgchXXt/UN5oNUDJMQn0LZGW+8OUojyKj8TFj0Bexapt6/rA/0+KVG/AXNJg69+Xi47IJmvQvgMd8w3JfjqRpbyUHbAQ5mvWtkB+TGpGLTgqysbbmUXFB0rNNBUqmO4IvNVa7YV5GcgyO/Sr8DokAAAzmSbS/0YV7LrVBYAP+9K5f0V+3imV1OXHXv9kXTScixEBJno0qgaAIv3L2bY98PIKMgg0j+cNU3vpfn2+eCwQUQsDJoFMW1dNgYhhPCEiIgIEhMTSUxM5MSJE3z11VfMmDGDCRMmYLPZvD08UcGdyDrBzC0zmZ48nWNZx5zbb6xzIwlxCQxqPohgv2AvjlCIcu7kZpg3AjKPFvYbmAQ3PFriRABnzdfilh0wlo+GW1LzVQjf4Or5pgRf3cj5g2DwfEaZSWu4ZfNQ5qt2GYWUHagQwt1Q8zUrX/2CCvIzlPqEhJb5Wpaar2k5l2+2pakeqtaBTc1yfebr6fP5zv/+5LdDNI4KoX871zSnWrRVLTlwe6ua6HQOnv/lRd7+820AekS344fAGIK2fq3u3OIe6PsBBIS65LGFEMIbrFYrmzZtYv369fz9999ER0d7e0iigrI5bCw9sJRpydNYcmAJDkWd41cxVGFE3Agebv8wLaJaeHmUQpRzigJ/fQorJhT2G6gHg2ZCrdL1G3DWfC1uw63Cy/0LbHYURfF47WXtSlHpkSKEb3HVfNOlwdf8/HwCAwNdeUifpjXc8kbZAS3z1VM1X6WAeMWi1Xw12xzkW+wumSQUNdsqXdYrFH2WzC7IfK0a7H/Zv0e5MfM15bwa0L2hQSR/HU7n2QXbqRMZRHy9iDId12JzsHSnWnKgUyMTt86+lTXH1gDwf83u5anj29ClrAGDP9z+H4gfIWUGhBA+67fffmPu3LksWLAAh8PBPffcw+LFi7n11lsBmY8K1zmaeZTPtnzGZ1s+41R2UbX6m+vdzMi2Iwk8Ekj/2/pjMpV+biNEpZCXDj88DvuWqLeb3QV3fVSmfgOlrfmqKOpawtPrVueVolKmTwifcK35Zkm5JPhqNpv5+OOPeffdd0lJSXHFISsEZ/DVKw23CssOeKrmq02CrxVJsJ8Bk0GH1a6QkWch0K/si1gt+BpWypIDUFTCo0xlB3LVzNdqV8h8jQpRg7Jns1wbfFUUhdOFwdc3727FW0v3smJ3Kg9/sYmFj3emdkRQqY+95sBZsgpshAXBqKU3czb/DKGmEP5oMoBWu34AxQ5VG6llBmq0ctEzEkIIz6tVqxbp6en07t2badOm0bdvX/z91e9tmY8KV7DarSzat4ik5CSWH1qOgjqXrhZUjRFtRzA6bjRNqjbBarWy5OgSL49WCB9wfAPMHwnnj6v9Bnq9CdePLnMigLPmq654690L16kFVrtH162KohSVHZDMVyHKvavNN0ur2MFXs9nMK6+8wooVK/Dz8+PZZ5+lf//+zJw5k5deegmDwcDYsWPLNJiKRgsQebfhlqdrvkrZgYpAp9MRHuTH2WwzGXkWYsLLHnzNKih78FX7LFnL8L6+duarut3VDbfO51udk66Y8ECm3NeWgVPXsed0FqNnb2LBozcS7F+682GLtp0E4Lj5BzKUM3Sr1pLFgTEE7/xO3aH1fXDHZPCv4pLnIoQQ3vLSSy9x4MAB1qxZw+TJkzEajTIfFS5xMP0g05OnM2vrLFJzU53bezToQWJcIv2a9sPPcPkTt0KIy3A4YN1HsHKS2m8gsoGaCFCzbB3DNVrwtbjLT5NBj1Gvw+ZQnGtXT7HaFewONUgsyUpClH+vvPIKgwYNIjw83GXHLPZKf8KECfzvf/+jR48erF27lkGDBjFixAj++usvJk+ezKBBgzAY5IvkQpbCrFPvNNwqDFI5PJT5apXM14omIsjE2Wyzy5puOcsOBJY+4d4VDbeuVfM1KtQ9ZQe0rNfIYD/n52T68Pb0+/gP9qZk8/Q3W/nfA/Ho9SXLAjiWeZpF248CfuQaV/Fu437869RudGf/AmMg9HkX2j0gZQaEEBXC0aNHmTlzJjfccAMbN26U+agoE7PNzPd7vycpOYlfj/zq3F6jSg1Gth3JqLhRNIho4MURCuGjcs/BwkfgwHL1dssBcOcUl/YbMJew7ACopQeyzTZnQoSnXPh40nBLiPIvISEBgIMHD3Lo0CG6du1KYGBgmepFFzsKMm/ePD7//HPuuusudu7cSevWrbHZbGzbts3jxap9hZad543gq0mvlR3wzFm9fAm+VjjhQWpw0lVNt4qCr6XPfPXXyg6UJfM1Vwu+Xj3zNc9iJ8dso0ops1H/SWu2VTMswLmtVngg/3uwPfcn/cWK3am8u3wfz/VuWuxjrj66mvvnvIvJ8QiKLoX1zeJpu28pKA6odh3cOxuimrlk/EIIUR5888031K1bl+XLlzu32Ww24uPj2bhxI4MHD/bi6ISv2Ju2l6TNSczeNptz+ecA0KHj9sa3kxCXwB2N78BkkDquQpTK0bUwfxRknwJjAPT+D8Q/5PJEAGfN1xIcNsCvMPhq8WzwVUtUMuh1XmnGLYQomXPnznHvvffy22+/odPpOHDgAA0aNGDUqFFERETw/vvvl/iYxY4Knjhxgvh4tRNhy5Yt8ff3Z+zYsRJ4vQpvlh3QMl8VBeclDu5kdpYdkOBrRRERpC46Mlyc+Vqmmq+Fs6sy1XwtLDtwpZqvwf5GggtrMZ3Jcl3pAS3z9cLgK0B8vQjeGdAagE9/P8SCzSeueSyH4uDtP97m1tm3YslpRXUy+aXqbNru/UkNvLZ9ABJ/k8CrEKLCOX78OJGRkRw7dozg4GD8/PwYO3YsgwcPZtmyZd4enijH8q35fLHtC26aeRPNPmnG5L8mcy7/HLVDazPx5on8/fTf/DTkJ/o37S+BVyFKw+GA1e/BrDvVwGvVxjB6JbR3T6NXc2HPkZIstbUSeVq/Ek9xXiVq1Ev8RAgfMHbsWEwmE8eOHSMoqKg3y3333Vfq+WaxU7rsdjt+fkXBCqPRSJUqUj/warzZcMt4wRk1q92BQe/eoGhR2QGp+VpRRBRmvmbmuibzNUvLfA0oQ83XwktJy5T5qpUduELNV1BLDxxJy+VMtpkG1V3zPXc6Uwu+Xlo/t3+7Whw8k8PHvx3khe92UK9qEO3rR172OOfyzjF84XB+OvATOiWQXlTh//yfp3pOFpiC4c7J0EYyv4QQFZPD4WDixInUrl0bKJqPNm7cmKNHj3p5dKI82p66naTNSXy540syCzIBMOgM3NnkThLiEujdqLfb58lCVHg5Z+G7BDj8m3q79WC443239huwlLDmKxRd8l/g4cxXabYlhG9Zvnw5P//8s3O+qSnLfLPYwVdFUXjooYecHb4KCgp45JFHCA4Ovmi/7777rlQDqYicPwgluRbCRS4M+No8kPmqBV+lhk3FERGsBl/TXVx2wBUNt8qU+Zpb2HDrCpmvoJYe0IKvrqJlvtb4R+arZtxtTThwJpufd6Xy8BebWfh4Z+pEBl20z/oT67l3/r0cO3+MIL0/C6reRc/Ud9DrFJSo5ugGzYbqTVw2ZiGEKI9effVVPvroI/Lz89HpdDzyyCNYLBYsFgv33HMPIPPRyi7HksM3O78hKTmJ9SfXO7fXD6/P6HajGdFuBDEhMV4coRAVyJHVsGA05KSq/QbueA/aDnV7vwFzKcoOaGtVj9d8tUiJPiF8SW5u7kUZr5r09HRnTLSkih18HT58+EW3H3jggVI9YGVi8Wbm6wVNe2xurvuqKIrUfK2AtLIDrm64VaayA4aylR2wOxTSc6/ecAsuaLrl0rIDas3XmPDLB1/1eh3/d19bBn66jt2nsxg9exMLHruRKv5GFEXhw/Uf8syKZ7A6rNwYVp+fA+tQ5fRS0MGOGnfTatSnYLo0q1YIISqSWrVqkZGRQWxsLDqdjn79+lGlShVWrVpFTEwMYWFh3h6i8KLNpzaTlJzE3B1zybZkA2DUG+nftD8JcQn0aNADvU6u0hLCJRx2WP0urHpbLXtVvSkMmuWxsleWUjTc8tcyX62e6YuiyZdEJSF8yk033cTnn3/Oa6+9BoBOp8PhcPDOO+9wyy23lOqYxQ6+zpw5s1QPUJl5s+GW4YLga1ku0S4Oq11BS64NMMoPSkXh6oZbWQU2oGwNt7TM19I2ksvMszjfq5FBV898BVya+ZqiZb6GXjlAGuRnZPrw9vT75E/2pWbz1FdbePfexiQsHsV3e9QsrtfrdOOFs3+jz9xGjhLAC9bRPD3gBQm8CiEqhWXLltG9e3dSUlLQ69XaeRs2bCA/P58///yThg0benuIwsOyzFnM3TGXpOQkkk8nO7c3imxEQlwCw9sMJ7pKtBdHKEQFlJ2ilhk4slq93e4BuP1d8Ls0U8xdShN89Vbma4EkKgnhU9555x26d+/Opk2bsFgsPPvss+zatYv09HT+/PPPUh3TNW28xWV5s+GWTqd2UrTaFWx295YduLBgub/UfK0wIpzBV9dkvma5IPPVXys7UMrg67nCrNeIIJOzKd3lOIOvLsp8VRTlig23/ikmPJCkYe2573/rWLn3DPHvf8Xfju8I1JlYU78n8YfXAJAe0pR70hIIrnkdDV1Ul1YIIcq7li1bsn//fj7++GNCQkLIycnhnnvu4fHHH6dmzZreHp7wEEVRWH9yPUmbk/h619fkWfMA8DP4MaDZABLjE7m53s3S2EYIdzj0K3yXCLlnvdpvQGu4ZdIXf63rveCr46LHF0KUb+6Yb0rw1U3sjqJsUG+UHQAw6vVY7Xb3B18Lf7x0uqLgmPB9RWUHyk/NVy2LvLRlB9JytHqvV6/TEhXq2szX8/lW5yTvSjVfL9Smdhi948/yw/qqKLnd6RRyiJ8jzxBSGHjl+gSeOtGXv8/m8HwbqVknhKgcrFYrvXv3ZurUqbz00kveHo7wgoz8DL7c/iVJyUnsOLPDub1ZtWYkxCXwYJsHqRZUzYsjFKICs9vg97dgzfuAAtEtYeBMr/UbsJSi5qvWHNrsrZqv0nBLiHLPXfNNCb66yYWXRZu8FJA0GXTkW8HqcG/ZgQKLevwAo0EyDCoQZ9mB3LIHXxVFcUnma1nLDpzLKaz3GnzlkgMAUSGFNV9dFHzVsl4jg/2ueblRjiWHRxY/wpwdcwgzDmGA4zres2wiJDUH/EPhro9IrdObP95aCcCdrSXTSwhROZhMJrZv3+7tYQgPUxSFP479QVJyEvN2z6PApv6mBhgDuLfFvSTEJdC5TmeZgwrhTlmnYP4oOLZWvR0/Anq/5dWyV+bSlB0oDH5qwVBPKar5KolKQpR37ppvSvDVTcwXZOZpTYI8TcsS9FTZgQD5MalQtMzXrAIbNrvjqpfpX0uexY6tMBU8NNAIlO49qWWRm0uZ+XquMPO12rUyX11cdkBrtnWtkgO7zuxi4LyB7E3bSwAGVjQ4y/XHFqt/oyHh982hVoNm/PTHERQF4utFUDvCc7W1hBDC2x544AE+++wz/vOf/3h7KMLN0vLS+Hzb5yQlJ7E3ba9ze6uoViTGJzK01VAiAiO8OEIhKokDK+D7hyHvHPiFQN8p0Gqgt0dVysxX79Z8lbIDQvgGd8w3JfjqJhdm5nmt7EBh0Le0WYLFJQXEK6YLM1TP51uvean+1WglB0wGHYEmAzabrVTH0TJfS1t2QKv5WrVK8TJfswpsFFjtZX5vF6fe6+fbPufRnx4lz5pHx+AarAioTcix9QD8ENCPZzLvod7CM3z3WCN+3H4KgL6S9SqEqGRsNhszZszgl19+IT4+nuDg4Iv+PnnyZC+NTLiCQ3Hw25HfSEpO4vu932Oxq7/bwaZgBrccTGJ8ItfHXC9ZrkJ4gt0Kv74Gf36g3q7RGgbNgqrlo7GhloxRkvwfbU6v1WD1FFkvC+Fb3DHfLFbwddGiRcU+4F133VXiQVREWsDTZNB5bYJo1JftEu3ikgLiFZPRoCc0wEhWgY2MvLIFX7MKikoOlOXzoJ3IsNgdKIpS4mOlOcsOXP25hAYa8TPqsdgcnM02UyeybNmlpzO14Oull2blW/N5YukTfLblMwBeiYpnfGYK+pz9EBAG/T+lY83uhH/8BwfO5DBi5ka2HMtEr4M+EnwVQlQiixYt4vfff6du3bqYzWbWrl170d91Op1zzirzUd+SkpPCrK2zmJ48nUMZh5zb42vGkxifyOCWgwn1D/XiCIWoZDKPw/yRcGKDertDItz2Gpiu3bvAUyylKTvgpczXfAm+CuFTdu7cSVxcHAD79++/6G+ljWcUK/jav3//Yh1Mp9Nht3v2i6y80n4MvJX1CkXlDrTLvd1F+zHxlx+TCici2I+sAluZm26dz1ODr6EBpa/3CkWZr4qiNrUzlrCkxzlnw62rZ77qdDqiQ/05np7PmeyCsgdfCzNf/9lsa/+5/QyaN4jtqdvxV3SsqtWVjie3qH+sfT0MnAHhdakBTB/enkFT17HpaAYAnRpWdWboCiFEZVCc+Wj//v1lPuoj7A47Kw6vICk5iUX7FmFzqFfFhPiF8EDrB0iIS6BdzXZeHqUQldDeJbDwUSjIBP8w6PcRNO/n7VFdwlxY+q40wdcCjzfcKkxWkoZbQviE3377zeXHLFbw1eHmhk0VkTPz1UvNtqCo5qvnyg5IzdeKJjzIj6Pn8sgoDJ6WllZ2ILQMzbagKPgKavZrSevQamUHql0j+Apq6YHj6fmkZpW96ZZW8zUmvChYOm/XPEYtGkW2JZsOgdVYEVCbUC3weuOT0H0CGIr+vVrXDuf9e9swZq66T9/WMWUelxBC+BKZj1YMJ7NOMmPLDD7b8hlHzx91bu9UuxMJcQnc2+Jegv2Cr3IEIYRb2Czwyyvw1yfq7Zg4NREgMtarw7oSc6lqvqprB48HX6XmqxCVntR8dROLTc02NXkx89XoqYZbWvDVKD8mFU1kYdOtjLJmvuYXlR0oiws/Txabg6Brx1AvUpT5eu0SCq5supWiZb6GBmK2mfn38n/z8caPAZhYrRUTzqehTz8MgZFw91Ro0uuyx7mzdQw5BTY2HEmnX9taZR6XEEII4Qk2h42lB5aSlJzETwd+wqGoQZPwgHCGtR5GQnwCLaNaenmUQlRiGX+rZQZOblZv3/AY9HgVjCWcbHuQxVnztfhrXWm4JYTwllIFX3Nzc1m1ahXHjh3DYrk4KPPkk0+6ZGC+zmIvP2UH3J35arbKZRQVVURhdDMjt2zB16wC9VLCsma+GvU6dDq17IClFO/rc86ar8XJfC0MvmaXLfNVURRn2QG7Po2bZt7OxlMbCVDg9xqd6JiyS92xbicY8BmEXT2oOrhDXQZ3qFumMQkhREUg89Hy72jmUT7b8hkztszgZPZJ5/au9bqSEJfAgGYDCDRdWg9dCOFBuxfBD2PAfB4CwqH/p9C0j7dHdU2lyXzV1qv5Fu8EX+VKUSHg5MmTPPfccyxdupS8vDwaNWrEzJkzad++PaCunydOnEhSUhKZmZl07tyZTz/9lMaNGzuPkZ6ezhNPPMGPP/6IXq9nwIABfPDBB1SpUsVbT+uaShx83bJlC3369CEvL4/c3FwiIyNJS0sjKCiIqKgomewW0gKefl4sO2DUa8FXz9R8lR+TiidcC766qOxAWGDZku11Oh1+Bj1mm8N5tru4Cqx2ss1qELhYma+haomAsgZfz+dbnZ+Rvt/cRKb5LB38I1gRUItQLfDaZRzc8hIY5GIEIYQoDpmPll9Wu5Uf9//ItM3TWH5oOQrqPLRaUDWGtxnO6LjRNK3W1MujFEJgM8Pyl2HDNPX2Bf0GfIG5FA23tCs1C0q4jigrabglhCojI4POnTtzyy23sHTpUqpXr86BAweIiIhw7vPOO+/w4YcfMnv2bGJjYxk/fjy9evVi9+7dBASoa/ShQ4dy+vRpVqxYgdVqZcSIESQmJjJ37lxvPbVrKnG0bOzYsfTt25eMjAwCAwP566+/OHr0KPHx8bz33nvuGKNPcl4GUcKGQK7kLDvg5hppUnag4oooLDtQ1oZbWS4qOwBFJzRKGnxNL8zeNRl0hAZcO8hZ3UWZr8czcgCwc55M81kmRDRlnd2P0MxjEFQNHlgAPSZK4FUIIa4gLi6OjAy12eCkSZPIy8uT+Wg5dDD9IM//8jx1/q8OA74dwM+HfkZBoXtsd74e8DUnxp7gvZ7vSeBViPLg3CH47LaiwGvnp2DEUp8JvAJYStNwqzDztcDDma9apq1cKSoqu7fffps6deowc+ZMOnToQGxsLD179qRhw4aAmvU6ZcoUXn75Zfr160fr1q35/PPPOXXqFAsXLgRgz549LFu2jOnTp9OxY0e6dOnCRx99xNdff82pU6dKPbbLzTddqcTB161bt/Kvf/0LvV6PwWDAbDZTp04d3nnnHV588UWXDs6XWcpB5qufx2q+qs/VX87kVTjhwVrmq2uCr6EBLgi+Fr6vS1p2oKjkgD863bVPirii5uuJrBM8tOBpAEy6k6yr1p5X00+ht+ZD/ZvgkT+gUY9SH18IISqDPXv2kJubC8Crr75KTk6OzEfLCbPNzNc7v6b7591p/FFj3v7zbVJzU4kOjub5zs9z8ImD/DLsF+5reR/+xmtfdSKE8ICd38H/bobT29R+A0PmwW2TLmr06gvMzpqvxb+P1HwVwj2ys7PJyspy/s9svnwC06JFi2jfvj2DBg0iKiqKdu3akZSU5Pz7kSNHSElJoUePojVyWFgYHTt2ZN26dQCsW7eO8PBwZ5kCgB49eqDX61m/fn2pn8Pl5puuVOJUK5PJhF6vfsNFRUVx7NgxmjVrRlhYGMePH3fp4HyZ1Zn56s2GW56p+Vpgkx+TiirC2XDLVWUHXJf5arWV7KRCWq7WbKt4jQOiQtRLGs6WMvN1+aHlDP1uKAVZ7emoO8H0oJnUP3sS0MHNz8LNz4FePjNCCHEtbdu2ZcSIEXTp0gVFUXjvvfewWq3897//pWrVqhiNRt566y0aNWrEvffeK/NRD9ibtpekzUl8vv1z0vLSANCho1ejXiTGJXJnkzsx+VggR4gKz5oPy16AzTPV28XsN1AeKYriTMQoSc1XrUxegYeDr1J2QFR0zZs3v+j2xIkTeeWVVy7Z7/Dhw3z66aeMGzeOF198kY0bN/Lkk0/i5+fH8OHDSUlJASA6Ovqi+0VHRzv/lpKSQlRU1EV/NxqNREZGOvcpjcvNN69UQ3bChAklPn6Jg6/t2rVj48aNNG7cmJtvvpkJEyaQlpbGF198QcuW0qVUo/0YeDX4Whgkd3vNV4vUfK2otIZbZS074I7gq8VeskmTM/O1GPVeAaJC1f3O5Vqw2h3F/izbHXZeXfUqr69+HQWF5/1NjNePJ8huhuAoGDAdGtxcorELIURlNmvWLCZOnMjixYvR6XQsXboUg8HADz/8QEREBIqisGDBAqpXr87atWtlPuom+dZ85u+eT1JyEmuOrXFurxVSi1HtRjGy3Ujqhdfz4giFEFeUdgDmPQSpOwEd3PQv6PaCz5a9stoVlMIlbonKDngt81WNDUjwVVRUu3fvplatohM5/v6XX3M7HA7at2/Pm2++CajxxZ07dzJ16lSGDx/ukbFeyeXmm0bjpd+ROp3OM8HXN998k+zsbADeeOMNhg0bxqOPPkrjxo2ZMWNGiQdQUWnZpv5eLDug1Zt1d81Xs03O5FVU4S7KfM0qcF3wVQuCmktY8/VcjprBWi24eJmvkUF+GPU6bA6FtBwzNcOu3Y05JSeFIQuG8NvfvxGswC9V23DDuVWgg+PhHakz+kuoEnXN4wghhChy3XXX8fXXXwOg1+tZuXIlx44dIzs7m1tuuYUzZ84wbNgw1q5dy9mzZ2U+6mI7UneQlJzEF9u/ILMgEwC9Ts8dje8gMT6R3o16Y9T7ZgBHiEph2zeweCxYc9V+AwOSoOGt3h5VmVxYfqwkma/Omq9eynyVK0VFRRUSEkJoaOg196tZs+YlWbLNmjVjwYIFANSoUQOA1NRUatas6dwnNTWVtm3bOvc5c+bMRcew2Wykp6c7718al5tv/jPDtixKPFO6sK5CVFQUy5Ytc9lgKhLtkmjvlh3wTOZr0Zk8yXytaC7MfFUUpVi1Ui9Hy3wNdUXmaynf1+dytczX4gVf9Xod1UP8OX2+gNSsawdff//7d+5fcD8pOSl0MASzPLAWYeeO4EDP+9aBNOr6MnUk8CqEEGXiKDyhfOFkWOajrpdryeWbXd+QlJzEXyf+cm6vF1aP0XGjGdF2BLVCfe9SZSEqFUseLH0Gtnyp3q5/k3oFVkjpgxPlhfmC4GlJcp20BtFWu4LN7nCul92tQBpuCQFA586d2bdv30Xb9u/fT7166pUzsbGx1KhRg5UrVzqDrVlZWaxfv55HH30UgE6dOpGZmcnmzZuJj48H4Ndff8XhcNCxY0eXjNPhhgRGiZa5iVlruOXF4Ksz89XdNV/lTF6FFVmYJWq1K2QV2Ep9HLeUHShh5mtajlbztfgNP4rTdMuhOHhzzZt0/7w7KdkpTKhSj3VKEGHZKRBSk3GBr/OJvT81wi5fL0YIITzl5MmTPPDAA1StWpXAwEBatWrFpk2bnH9XFIUJEyZQs2ZNAgMD6dGjBwcOHLjoGOnp6QwdOpTQ0FDCw8MZNWrUJQ0Jtm/fzk033URAQICzCZYrHTp0iCeeeIIePXrQo0cPnnzySQ4dOuTSx6iskk8n88jiR6j5fk1GLRrFXyf+wqg3MqDZAJYNXcahJw/xcteXJfAqRHl3Zi8k3VoYeNXBzc/DsB8qROAVLizxp0NfisxXgIISriXKQjJfhVCNHTuWv/76izfffJODBw8yd+5cpk2bxuOPPw6ol/Q//fTTvP766yxatIgdO3YwbNgwYmJi6N+/P6Bmyvbu3ZuEhAQ2bNjAn3/+yZgxYxg8eDAxMTEuG6ur55slznyNjY29avbb4cOHSz2YisTZcMubZQcKa77aHG6u+Vr4Y+IvPyYVToDJQFSIP2eyzRw6m0Nc3YgSH8Nsszuzo12S+VrK4Kuz5msxyw4AVA8JAM5z5gpNt87lnePB7x9k6cGlVFFgeXhzOmWeUP/YqAdK/6n8/PZmwE7NsIASjVcIIVwpIyODzp07c8stt7B06VKqV6/OgQMHiIgo+l5/5513+PDDD5k9ezaxsbGMHz+eXr16sXv3bgIC1O+woUOHcvr0aVasWIHVamXEiBEkJiYyd+5cQM1O6NmzJz169GDq1Kns2LGDkSNHEh4eTmJiYpmfx88//8xdd90F4BzTH3/8wUcffUSNGjUIDFSvUpD5aPFlmbOYu2MuSclJJJ9Odm5vFNmI0e1G81Dbh4iuEn2VIwghypUtc+Cnf4EtH6pEwz1JFa7fgLlwbeFXwrX2hSUB8y12qvi7v2SK1e5wrsflSlFR2V1//fV8//33vPDCC0yaNInY2FimTJnC0KFDnfs8++yz5ObmkpiYSGZmJl26dGHZsmXOeR/AnDlzGDNmDN27d0ev1zNgwAA+/PBDl41Tm2+2bduWzp07A/Dnn3/SokULfvzxR2677bYSH7PE3zZPP/30RbetVitbtmxh2bJlPPPMMyUeQEVlveBsnLcYCx+7pEGqkiqQ7o0VWtOaoZzJPsve09mlCr5m5asZszodhLhgglNUdqCEwdfcwpqvJcl8LWy6dbng67rj67hv/n0czzpOR0Mgy/1rEpp5AnQG6D4ebnyK8wU258mJGhJ8FUJ40dtvv02dOnWYOXOmc1tsbKzzvxVFYcqUKbz88sv069cPgM8//5zo6GgWLlzI4MGD2bNnD8uWLWPjxo3OMlQfffQRffr04b333iMmJoY5c+ZgsViYMWMGfn5+tGjRgq1btzJ58mSXBF+ff/55xo4de1EdMICFCxeybds2LBaLzEeLQVEUNpzcwLTN0/h619fkWfMA8DP4cU+ze0iIS6Bb/W7odRIoEMJnmHNgyb9h21fq7Qa3wD3TKmS/AUsprzLV6XQEmgzkW+0eq/t64ePIelkIuPPOO7nzzjuv+HedTsekSZOYNGnSFfeJjIx0nvh3B22++Z///OeS7c8995xngq9PPfXUZbd/8sknF126VtlpAU/vNtzSMl/dHXwtrPnqxecq3KdZjRBW7z/L3pSsUt1fKzkQ4m9EX5Lrgq6gzJmvxaz5CkVlB85mF5UdUBSFKX9N4dlfnsVmtzExuBYTCszoc9MgtDYMnAF11Vozp8+r94sM9pPJlhDCLbKzs8nKKvp+9vf3v2yH2UWLFtGrVy8GDRrEqlWrqFWrFo899hgJCQkAHDlyhJSUFHr06OG8T1hYGB07dmTdunUMHjyYdevWER4eflH9/x49eqDX61m/fj13330369ato2vXrvj5FX3X9urVi7fffpuMjIyLMm1LY8+ePXz77bc0btz4ou233347rVu35v3335f56FVk5Gfw5fYvSUpOYseZHc7tTas1JSEugWFthlHt/9m77/AoyvWN49+t2VRCaAEsoCJFUBAbVlQUBWyAlWNBxQbHgu3gUUE9R9RjVxRFBc9PPSqKHVFEEQs2BAsIClJEekkl2Tq/P3Znk0hC2mxL7s91cV1usjP7rptk3nnmmfvNaJ3AEYpIg2xcDNMvgi2/gs0Ox94CR14P9qZ5fmZ2vjbkXNvjsse1+Go2Ythsia0NiEjdmfPNv7r44ot5+OGHG7RPy377Tz755OgKZVK58zWBC27ZzczXWC+4pQDxpqxrfjYASzcUN2j7aN5rRuMjB6DiCre3Hp2vhmFUKr7WJ/M13K26qSjc+VpQXsCwV4cx9sOxZAQDzM/ZlwmlxdiDPtj3ZLjis2jhFWB9YRmAIgdEJGZ69OhBixYtov8mTpxY7fN+//13nnzySbp06cIHH3zAlVdeydVXX83zzz8PwIYNGwBo167q7eXt2rWLfm/Dhg07rfrqdDrJy8ur8pzq9lH5NRqjTZs2LFq0aKevL1q0iLZt22o+Wg3DMPhs9Wdc8MYFdHiwA1fPupqfNv2Ex+nh/P3P57ORn7HkqiWM7TdWhVeRVGMYsGBaON91y6+Q3QEueg+OvrHJFl4BfMHw+Wd9YwegIne1LF6dr75Q9HUbunixiMRXbfPNhrAs5OS1114jLy/Pqt2lPF+k4JnI4quZN1vfVeHrS7EDTVu3/BwAlq4vwjCMek8aisrDxdccjzXFV1cDOl+LvYHo7Un1yXyNLrhV7GXBugWcOf1MVhas5DB7GrPS2tOiaAPYnTDgDug3OnxJuxKz81XFVxGJlSVLltCxY8XiR9V1vUJ41daDDjqIu+++G4A+ffrw888/M3nyZC688MK4jNUKo0aN4rLLLuP333/n8MMPB8IZXPfeey9jx47VfLSSLTu28N8f/suU76ewdMvS6Nd7te3FZX0vY0SvEbRMb1wnsogkUHkRvHst/By54LTPCXDGU5DZKqHDiodo5msDzrU9kYahMl98O1+12JZI6qhtvtkQ9S6+9unTp0rxxTAMNmzYwObNm3niiScaNIimyCwMNeRqnFVcZudr3GIHdEBpivZum4nTbqOoPMD6wnI65KbXa/sis/PVgsW2oGGZr2bXa1aas14XCczM15Vbt3L4c2fhC/iYkJ7PbV4f9h3boMUecOZU2O2gardfX2AWX+v3/0xEpK6ys7PJycmp9Xnt27enR48eVb7WvXv3aJdofn54BeyNGzdWyVPduHEjvXv3jj5n06ZNVfYRCATYtm1bdPv8/Hw2btxY5TnmY/M5jXHbbbeRnZ3NzTffjN8fPr64XC7atm3LE0880eznoyEjxNxVc5ny/RRm/DIDXzB8/Mt0ZXJOz3MYdeAoDul4iLqvRFLd+h/CMQPbfg+vNzBgPPT7e5Pudq3MvAMurQELWJnnrOUxXhfFpEYlkdRjzjcfeOABxo0bB0CHDh2YMGECV199dYP2We/i62mnnVZlwma322nTpg39+/enW7duDRpEU5QUsQMNXJiovsoD5gGleRzsm5s0p4O92mTy68YSlm0ornfxtdDq4msDOl+3loRjA+qT9wqQmRZeLKy43EaGJ8CnWXtxWMmW8De7DYHTHodddA2Zna9abEtEEu2II45g2bJlVb7266+/sueeewLhxbfy8/OZM2dOtNhaVFTE119/zZVXXglAv379KCgoYMGCBfTt2xeAjz/+mFAoxKGHHhp9zj//+U/8fj8uV/jv/uzZs+natWuj814hvAjDddddR2FhIT5fuLCYlpbW7OejG0s2Mm3RNJ5Z+AzLty2Pfr1v+76MOnAU5/Y6l5y02ov0IpLkDAO+fQY+uAWCvvB6A2dOhd0PSfTI4qoxna/pCep81bmySOow55vXXXcdxcXh+MXs7OxG7bPexdcJEyY06gWbi2jnqyNxnQXOyGsrdkAaq1t+Dr9uLOGXDUUc261+GSdm56tVsQNpDSi+bjHzXusROfDTxp8Y/urZGNxLH9tKpqXtRm7JFnC44cR/wyGjdooZ+Csz87VDroqvIpJY1113HYcffjh33303Z511Ft988w1PP/00Tz/9NBCeZF577bX861//okuXLnTu3JnbbruNDh06cPrppwPhTtmTTjqJUaNGMXnyZPx+P2PGjOGcc86hQ4cOAJx33nnccccdXHLJJdx88838/PPPPPLIIzz00EOWvh/NR8NdrrNXzObp75/m7WVvEwiFLxhmu7MZ0WsEo/qO4sD2ByZ4lCJimfJCePvvsOSt8OOug+C0SZDR/KJWzDixhixgZd7+H+8Ft7Q+ikhqamzR1VTv4qvD4WD9+vU7hcxu3bqVtm3bEgzG549YsjO7TRMbOxB+7UAMO18Nw6iIHVDxtcnq1j6bt3+AZQ1YdMvqBbdc0YsK9eh8LTU7X+u22Na0RdO46r2rKPeXcafzDW52vInLG4SWncPdBR361Gk/G8zO1xzFDohIYh188MG88cYbjBs3jjvvvJPOnTvz8MMPM2LEiOhzbrrpJkpLS7nssssoKCjgyCOPZNasWXg8FReQXnzxRcaMGcPxxx+P3W5n2LBhPProo9Hvt2jRgg8//JDRo0fTt29fWrduze23385ll11m6ftpzvPRP4v+5LmFz/HswmdZXbg6+vXDdjuMUQeO4uz9zibTnZnAEYqI5f5cANNHQsFqsLvghDvgsKtqbQRoqrz+hi+4ZXagxqv4Wu5T5quINKD4ahjVd1F6vV7c7vrd0tuU+ZIgdiBapArFrvPVW6n7ULdSNF3d8sNXe5aub0Tx1eLYAW+9YgfCna+ta4kd2OHfwd9n/p3nFj1HnmHjk4w9OHRHOA9x4+6DaDdiMnha1Ok1DcOIxg6o81VEksGQIUMYMmRIjd+32Wzceeed3HnnnTU+Jy8vj5deemmXr7P//vvz2WefNXicddHc5qOBUID3f3ufKd9P4b3f3iNkhI+BuZ5cLtj/Ai498FJ6teuV4FGKiOUMA76eDB/eBiE/5O4Bw6fBbn0TPbKEquh8rX9B02wYKotz56salUSatzoXX82uBpvNxjPPPENWVlb0e8FgkHnz5jXLjK2amLdEJ0Pmayw7XytfMdQBpenqlh/OiVuxuQRfIFSvq8xFZeHbIHMsW3Ar/HPmq9eCW5HO18yaO1+XbVnGmdPP5KdNP3EUTt5Na0fOjgL8uJjgP5/9e13L2XUsvEK46GxOttrlqPgqImKF5jYfXV2wmmcXPstzC5/jz+I/o18/ao+juKzvZQzrPox0l+6uEGmSdmyDt8bAsvfCj7ufAqc+Dum5CR1WMmhU5muci6+6S1REoB7FVzOryzAMJk+ejMNR8cfD7XbTqVMnJk+ebP0IU1RSxA7EIfPVPJg47baEFpolttq38JDjcVJUHmDF5hK6t6/7oh2F0czXejfaV8vlDP9c1yvztTSS+VpD5+srP7/Cpe9cSqm3hH+58xjnD2H3FkOrfXg89xZeXOwhv9hXr3GaXa95mW5NtkRELOD3+7n55ptp3bp1k56P+oN+3vn1HaZ8P4UPln+AQXge1yq9FRf1vohLD7yUbq2bToFZRKrxx7fw2kgo/KNe6w00F2YThrsBd156opmvsV2U2hTNfNX5gEhK8Pv9nHTSSUyePJkuXbpYtt86V0NWrlwJwLHHHsuMGTMsWbG2KTMLng25GmcVZyTztT7ZmPWl2yiaB5vNRrf8HL5ZtY2lG4oaVHy1LHbAUf+f62jn618yX70BL2M/GMsT3z1BG8PGHE9HDimPRCv0OguGPEhw7jpYvJxNxd56jdNcbKt9C3W9iohYweVykZWVxccff8xll13WZOejd392NxM+nRB9fHzn4xl14ChO73Y6ac66ZZeLSIoKhWD+4zDnDggFIusNTIMOvRM9sqTSqM5Xd3wX3CpX8VUkpbhcLn788UfL91vvVrRPPvnE8kE0RWZXXiI7X52RztdATDtfzeKrul6bum7ts8PF1/XFULf1pgAoKre2+Gqualqfztdo5mtmRefr79t/56zpZ7Fg/QKONhy8425DTnkxONNh0H3Q53yw2WibEz7R3VRcXq9xmp2vKr6KiFjnb3/7G88++2yTno/+bf+/8dSCp7jwgAu59MBL2Ttv70QPSUTioXQrvHkl/PZB+PF+Q+GUR8BT96aH5sIXWVQxrUELbkViB3xxynw1F9xyq/gqkirM+eY999xj2T7rXXwdNmwYhxxyCDfffHOVr9933318++23TJ8+3bLBpbJkWHDLvBIYCMU+87UhYeeSWszc16Ub6rfoVjR2wOIFt+pVfI3GDoQLqW8tfYsL37yQ4vJCJrpyuTlgYPPtgNZdw90F7XpEt22bbRZf69n5WmAWX5XFJyJilUAgwHPPPcdTTz3FvvvuyxFHHFHl+/n5+Sk/H907b2/+uO4PHHbNrUSajdXz4fVLoOhPcKTByfdC34sUM1CDaOer0w71rKGaTUPx7nxNU7OSSMow55sfffQRffv2JTMzs8r3H3zwwXrvs97F13nz5jFhwoSdvn7yySfzwAMP1HsATZU/WnxN3AHTGb09O/aZr7qS1/R1zc8GYOmGojpvEwwZFJeHF9yyqvPVvKBR1wW3AsEQ23f4ImOwcf0H1/PgVw/SzrAxO609B3tLw0/sPQIG/QfcVf+wto0slrWpqL6xA+Hia746X0WiQqEQBQUFdX5+bm4udrtOVqTCzz//zIEHHsgXX3xBKBRi4cKF0e/ZbDYeeeSRJjEfVeFVpJkIheCLh+Djf4MRhFb7wJnPQ37PRI8sqZnnAWkNKL7Ge8EtZb6KpB5zvgnw66+/VvmerYEXxepdfC0pKcHt3nnRGpfLRVFR3YsyTV0yxQ7EMvNVsQPNh1l83VjkZXupj5aZ1S9eVVlxJHIAIMeTmM7X7Tv8GAbYgDOmD+SrP7/kOMPBG67W5HhLwZUBgx+E3udWu73Z+bq52IthGHX+Y2tmvnbIVfFVxFRQUMCD7y7Ek5ld63PLS4sZO6QPeXl5cRiZpAozbiA9PZ0XXniBrl27Vvn+0qVLNR8VkdRQshneuAxWfBx+vP/Z4TlpWlZix5UCGpX56opv5quKryKpJxbxVvX+a9WrVy9eeeWVnb7+8ssv06NHj2q2aJ7MgmciF9xyRbqF4pL5qtiBJi8rzckeeRlA3aMHisrCXa/pLodlFyLc9ex83Voa7lgN2or4du2X3GvP4SOyyPGXQdsecNncGguvAG0ixVdfMETBDn+Nz/urDWbna45iB0Qq82Rmk5mTW+u/uhRopfnad999+fe//01ZWfhCl2GE5zqaj4pISlj5GUw+Mlx4dabDqY/DGU+p8FpH0c7XBjQAeaLF19g1KFUWXXBLd4qKpJzly5fzwQcf7DTfbIh6d77edtttDB06lBUrVnDccccBMGfOHP73v/+ldL6W1cyuvERmvkY7X2OZ+RowO191MGkOuuZns2bbDpZuKKLf3q1qfb6Z92pV5ACAqx6dr4FQgP98NhnYj1as5g13W/r6ygEDDrwwnKfl2nVxNM3pIDfDRcEOP5uKvXXq+DUMIxo7oM5XERHrbN26lbPOOosff/yRH3/8kZKSEk477TSeeeYZtm7dym+//ab5qIgkr1AQ5t0Pn94DRgjadAuvN9C2e6JHllK8kXPQhjQ6eeIdO+DT+bJIqjHnm5988gk2m43ffvuNvfbai0suuYSWLVs2KOKq3n+tTjnlFN58802WL1/OVVddxfXXX8/atWv56KOPOP300+s9gKbKF+k2TWTsgFn4jW3na7gApoNJ89DdzH1dX7fO11gUX9OiWca7Lr6uL17PCf93Ai//+B7H2H/g47RHw4VXdxYMexZOfbTWwqupYtGt8jo9v7DMH53QtctR8VVExCrXXXcdLpeLP/74A4/Hw+rVq7nqqqv48ccfWb16teajIpK8ijfC/50Oc+8OF157/w1GfazCawOYTRhpDTjXNjtQzaJorOl8WST1mPPNNWvWkJGREf362WefzaxZsxq0z3p3vgIMHjyYwYMH7/T1n3/+mZ49FQ4OlRfcSmTxNdz5Gohh5mvFlTxlvjYH3drnALB0Yx1jByKZrznpDfpTU626ZL5+svITzn39XLaWbOR+xwFc47g3/I38XjB8GrTep16v2Tbbw68bS+q86JbZ9ZqX6dZES0TEQh9++CEffPABu+22G06nk+nTp7PXXnvx+++/s//++3PMMcdoPioiyWfFJzBjFJRuBlcmDHkQDjgn0aNKWd5GrK/iiWxj3sEZa8p8FUk9leeblXXp0oXVq1c3aJ+NrpgVFxfz9NNPc8ghh3DAAQc0dndNRnTBrUTGDtjNbMwYdr4qdqBZMRfd+nVDMcFQ7T9Xseh83VXxNWSE+Ne8fzHg/wbgKtnEN67WXMNKAL5pPRQu+ajehVeo3Pla1+JrOBOmfQt1vYqIWKm0tLRKB4Lpjz/+wDAMzUdFJLkEA/Dxv+D/zggXXtvuF15vQIXXRvFa0PlaHrfOVxVfRVJNTfPNbdu2kZaW1qB9NrgyOG/ePC644ALat2/P/fffz3HHHcdXX33V0N01OdEFtxIaOxDpfI1l5mv0Ngp1vjYHnVplkua0U+YPsmbbjlqfbxZfc6zMfHVUf1Fhy44tDHpxELd9chsnh+z84mhFH7+PcnsmV/mu5uvut4CrYcXQNjn1ix0wO19VfBURsdZRRx3Ff//73+jjb7/9lvPPP5/jjz8eu92u+aiIJI+idfDfU2HefwAD+l4Eo+ZAm30TPbKU521Eo1N6vDNfowtu6XxZJFX8db5ps9kIhULcd999HHvssQ3aZ73uBd6wYQPTpk3j2WefpaioiLPOOguv18ubb76plWUrCYUMApGuQLMAmgjOOGS+enUlr1lx2G10zc/mx7WFLNtQROfWmbt8flFMO18rJkxfrPmCs187m01Ff/KwPZNrDAcEfdC+N3c4rmfmcgdHZjXsChWEYwegHp2vBWbxtW6ZsiIiUjf33Xcf/fv359VXX6WkpIQLL7yQjIwMgsEg06dP56STTkr0EEVE4LeP4I3LYMfW8HoDpzwCvYYnelRNRvQuU5edus3OK5h3bJpNRLGmBbdEUs99993H8ccfz3fffYfP5+Omm25i8eLFbNu2jS+++KJB+6zz5ZdTTjmFrl278uOPP/Lwww+zbt06HnvssQa9aFPnq5Sx6kqCztfaFiZqDPNKng4mzUfXduHogV/qsOhWtPPVY2HxNdr5GsIwDB748gGOmXYMzqJ1fONsxTWhyM/ioVfCJR+y1NcKgFZZ7ga/ZrtI5+vmema+5qvzVUTEUuPGjcPv9+PxeDjyyCM59thjueqqq3A6neyxxx6JHp6INHdBP8weDy8OCxde83vB5fNUeLWYN9KE0ZDOV0+lzlfDiF2Tkqlc58siKadnz578+uuvHHnkkZx22mmUlpYydOhQFi5cyN57792gfda58/X999/n6quv5sorr6RLly4NerHmonKxM5GZr+bt2YE6ZHM2lA4mzU900a0NRbU+N5aZr/5AiDNeOYO3lr3FaYaTF+wtyQr4wdMCTnsCug8BYGuJD4DWjSi+mp2vG+sYO7ChKJz52iFXxVcRESvVNB+99957EzgqERGgcC28djH88XX48cGj4MR/NTj2SmrmsyDzFcLxBbE+jzU7bHWnqEhqadGiBf/85z8t21+di6+ff/45zz77LH379qV79+6cf/75nHOOgsKr4690m39iF9wKd74GQwahkIHdbn0EgnkwaciBT1JT98iiW8s21N75WlQeACwuvkZ+p4IGvL/0HR6zZTAGJ4QC0PEgGP4ctNwz+vytJeFu1VaZjYkdiGS+FnkxDAObbde/S2bsQH6OYgdERKz0+eef88QTT9CrVy+ys7PZZ599OPnkkxM9LBFp7pa9D29eCWXbIS0HTn0M9js90aNqsqKZrw04B/VU2qbMF4xp8TUQDEXvilXxVSS1bN++nWeffZZffvkFgB49ejBy5Ejy8vIatL86/7U67LDDmDJlCuvXr+fyyy/n5ZdfpkOHDoRCIWbPnk1xce2FmObCvBLntNtiUvCsK2elwq8/RotuRVdvdOtg0lx0jRRfV2/bQak3sMvnWr3glmEYTPvhGQD2sG3kW0cuY4zINaR+Y2Dk+1UKr2W+IKWRnKXGxA60jcQOlPmDlNTyng3DiMYOqPNVRMRaPp+Pt956i9atW7P77rvz66+/Mn78eAKBAJMnT9Z8VETiK+CDD/4J/zsnXHjt0CccM6DCa0xVdL7W/xzU6bBH4/nKA7FddKs8UHEOrvNlkdQxb948OnXqxKOPPsr27dvZvn07jz76KJ07d2bevHkN2me9LxVlZmZy8cUX8/nnn/PTTz9x/fXXc88999C2bVtOPfXUBg2iqTFjB1wJ7HqFql23sVp0K5r52oADn6SmVllptMlOwzDg1427Psm1csGtYm8x575+LmM/vIZB9q94130L+wcDkN4Szn0FBv4bnFULrFtLw12vbqedrLR6rS9YRYbbGd2+tkW3Csv80d+LdjkqvoqIWGn06NGcffbZrF69mu+//56tW7eyePFi9t9/f5588knNR0UkfravgqknwfzHw48Puwou/hDyOid0WM1BNPPV2bBGp2juqy/GxVd/xf51p6hI6jDnmytXrmTGjBnMmDGD33//nXPOOYfRo0c3aJ+N+gvQtWtX7rvvPtauXcv//ve/xuyqSfFFi6+J63oFcFZ6/VgVX72R2AFlvjYv3eoYPWBV5uuPG3/koCkH8ebPr/AkLp5wP0qOrQx/h0Pgis+ha/WrW0fzXjPdtUYF1KZy9MCumF2veZlu/V6IiFhs+fLlXH/99TgcFX9fe/TowauvvorD4dB8VETi45d3YPLR8OeC8HoD57wEJ03cqRFArGcYRqM6X6EiAqDMH9viq1nc9bjsjT4XEZH4qW6+6XA4GDt2LMuXL2/QPi25/OJwODj99NN5++23rdhdyvNFM2gSW3hxVoo8iFnsQKDigCLNh1l8XbqL4qthGNHO15z0hnedPrfwOQ595lCMLctZYM/lCsKF3EmBU9k0fAa02K3Gbc3O11ZZDc97NbUxi6+1LLq1vjC82Fb7Fup6FRGx2oEHHhjN3qrsl19+oXfv3pqPikhsBbww8yZ45W/gLYTdDg43AnQbnOiRNRuBkIG5nnRD11cxGyTM9UtiJRrRp4YMkZSyq/nmAQcc0KB9NrwiIjUyYwfcCe58tdlsOO02AiEjOiar6YDSPHXLzwHgl/VFNT5nhy9IIDIzakjn6w7/DkbPHM20RdM413DyjC2HjFAIMlpzeellfBDoyaDQridcWyKdr43JezW1jUQIbK4ldsDsfFXxVUTEGj/++GP0v6+++mquueYali9fzmGHHQbAV199xaRJk7jnnnsSNUQRaQ62/Q7TR8L6ReHHh18Nx98ODusWlpXa+SrlqDb0Vv70aPE1xp2vOlcWSRmxnm+q+BoD5gHBlQS5Lk5HuPga68zXNB1QmhVz0a1lG4sxDKPa22jMyAGXw1bvCcfSLUsZ/upwft+0mCmkcykuMEKw55Ew7Bm+feRn8Ppqvahgxg60ymx852s0dqC24muBWXxNb/RriogI9O7dG5vNhmFUzGVuuummnZ533nnncfbZZ8dzaCLSXPw8A96+GnzFkJ4HZ0yGfQcmelTNkrdS8dXdwPNtjzs+ma/R2AEttiWS9GI931TxNQZ80c7XxBdfXQ475f5QDDtfzczXxL9XiZ992mbhsNso2OFnY5GX/Gq6PIvKI5EDHle9Mo5e+uklLnvnMnb3lbHA3oLuIQOwwTE3wdE3gcOJ27EEqHrluzpbS8KF0tYWdL62yzEzX2uLHQh/v7r/JyIiUn8rV65M9BBEpLnyl8MH4+C758KP9+gHw56FFh0TO65mzJz/O+02HPYGLrgVKdqaEXqxUh4ZqxanFkl+sZ5vqvgaA/5Il6krSYqvQPT2b6uZt2poYaHmxeNysFfrTH7bVMIvG4qqLTQW7qjfYlvlgXKum3UdkxdM5gLDxWRbDumhEGS2hWFTYK/+0eeaV7m9tRVfSy2MHcgOv8eNtSy4taEonPnaIVfFVxERK+y5556JHoKINEdblsP0i2DjT4ANjhoL/W8Bh06hE8kbKZg2tOsVID3Ona/p6nwVSXqxnm/qyBEDSRU7ELkaGKvOV2+k81U5Ns1P1/xsfttUwrINxRzbte1O3y+MLrZVe/F1xbYVnDn9TJatX8hU0rnIjBnofAwMnQLZ7ao83xXJU66t83VLpPPV2tiBWjpfI7ED+TmKHRARiYV169bx+eefs2nTJkJ/WVD06quvTtCoRKRJ+fFVeOda8JdCRmsY+jTsc3yiRyVUzP8bmvcK8ct81fooIqnL6vmmiq8xYBY605Ko89Ufg8zXYMiIRiyo87X56d4+h3d/XM/SGhbdKioPALUXX2f8MoORb41k9/ISFtpy2NcAbHboPw6Ouh7sO/9suSO37tQ589WSBbdqz3w1DCMaO6DOVxER602bNo3LL78ct9tNq1atqsTa2Gw2FV9FpHF8O+D9m2Dh/4Ufdzoq3AiQ0z6x45Io8863xnS+eqLF19g0KJnKdJeoSEqKxXxTxdcYMAtCLmfDMmis5Ix0CAZi0Pla+UqhMl+bn26RRbeWbiiu9vtm52tNsQP+kJ8bZt/Ao988yiW4mGTLJs0wILs9DHsGOh1Z42ubk61aM19LzczXxne+tonEDhSXByj3B6udRBWW+aOTrHY5Kr6KiFjttttu4/bbb2fcuHHY7Zp7iIiFNi0Nxwxs/oXwegM3h9ccqKYRQBLHG+18bfjnYs7jy2Lc+arYAZHUFIv5ZlLMWidNmkSnTp3weDwceuihfPPNN3Xa7uWXX8Zms3H66afHdoD1ZB4QkinzNRadr1WKrwoRb3a6RoqvKzaXVFsErSi+7nyNZ03hGm5dfivPffMoL5DOM6SHC6/7DIArPt9l4RUqusp9u7ioYBiGpZ2vOR5n9PamTTXkvppdr3mZbl3hFhGJgR07dnDOOefEpPDa1OajIlIPC1+EKceGC69Z7eCCt+DYcSq8JiFLMl/jVHw1F/TyJEEcoYjUXSzmmwn/K/DKK68wduxYxo8fz/fff88BBxzAwIED2bRp0y63W7VqFTfccANHHXVUnEZad2bnqzsJiq9m5msgFIPO10DF+7Q3cKVJSV0dc9PJTnPiDxr8vqVkp+8X1dD5OvO3mRzy3CF4Sn/je1sOI3CBzQEDJsB50yGzda2vbXaV7yp2oKgsEF1oLi+z8cVXm81WKXqg+tzX9YXhxbbaV7MAmYiINN4ll1zC9OnTLd9vU5yPikjtHMFyHG+PhreuAv+O8AKvV3wOex2T6KFJDazIfDXv2ox55qs6X0VSUizmmwmPHXjwwQcZNWoUI0eOBGDy5Mm89957PPfcc/zjH/+odptgMMiIESO44447+OyzzygoKIjjiGvnT6IFt8zO10AMOl/N2ygUOdA82Ww2urXP5ttV21m6vphu+TlVvm8WX3M84eJrIBTg9k9uZ+JnE7kCFw+TRZoB5HSE4c/BHofV+bXNCxveXcQObIlEDmR7nI26Lamyttke/thWVmPuq9n5quKriEhsTJw4kSFDhjBr1ix69eqFy1X1At+DDz7YoP02xfmoiNRi0xKOWTYeu3d9eL2BY2+BI8eq2zXJWZH5Gq8Ft8q04JZISorFfDOhxVefz8eCBQsYN25c9Gt2u50BAwYwf/78Gre78847adu2LZdccgmfffbZLl/D6/Xi9VYUSoqLw/mUfr8fv9/fyHdQvTJfeKEhl42YvUZdmc23ZV7r329JWfj/q8fliOv7NF8r0f9vBbq0zeTbVdtZsq6AwT3bVvne9h3hn48st53V21Zz/pvn88Oaz3iFdM4i/McruPcJhE6dBBl5UI/P0+zo3tXP9caCHQC0ynRb9rPSOjM87vUFO6rd59ptpQC0y05r0j+f+h1MfYn6DP1+P4YRJBSq/WTHMILRY3VT364hmuvv38SJE/nggw/o2rUrwE4LIDREPOajkJg5qcSOjoUpzDCwLXoB54fjyA6UE8rKJ3TG0xh7HA7BUPifJK0yb/h3zu2wNfj30GxELS0PxPR3uDQ6Vv2tqIn+ltasPvNKSMxcNhBomndAx2K+mdDi65YtWwgGg7Rr167K19u1a8fSpUur3ebzzz/n2WefZdGiRXV6jYkTJ3LHHXfs9PV58+axZMmSeo+5Ln5eawMcbFj/JzNn/hGT16ir4gIHYOObBQvwr7K2+3VlMYCToK+cmTNnWrrvupg9e3bcX1Oq8m8O/6x/9tPv7BdYXuV7q9aFf/bmfP8Ooz++nX38xSwkm72wEcLBko5nsSL7JJj7Vb1fd8smO2Dnh59+JnfLT9U+Z9HW8NhsvlLLfj7LtoVfd/6iJbTe9vNO31+wPPz9wg2rmDlzpSWvmcz0O5j64v0ZFhcXs+JPO57M7FqfW15azOzyFWRnZzf57Rpiy5YtDdou1T3wwAM899xzXHTRRZbtMx7zUUjMnFRiT8fC1OIMlnHAH1PZbXt4/rkxe3++3/MyfD8XwM/xP5+R+vt2U3iOX7hta/T3r76/h8s3hPexam1sz9eXrwyfG6xa8Rszy3+N2es0BfpburP6zCshMXPZ+eua5nw0FvPNhMcO1EdxcTHnn38+U6ZMoXXr2nMhAcaNG8fYsWOjj//880969OjB0UcfTadOnWIyzuUfL4c/fmevTnswaFCPmLxGXb2y8TtWFG+j1/69GXRAe0v3/eWKrfDzAvJaZDFo0BGW7ntX/H4/s2fP5oQTTtip/VviK39NAdOnfMO2UDqDBlXNxnp8xRdQXMr/Nj7LKHsZD5CFCzBa7I7vlMmsWLy1wZ/h3LKfWLh1Pft07cagIztX+5zt3/wBv/7CPru1Y9Cg3g14dztb8+nvzNuwnOy2uzFoUM+dvv/K1O9g8zb6H3wAg3p3sOQ1k5F+B1Nfoj7Dbdu2sfKz38nIzq31uTuKCzjhqL3Iy8tr8ts1xKpVqxq0XapLS0vjiCPiN+eoTkPmo5CYOanEjo6FKWjDTzjfuATb9t8xbA78R/+Drwq7cMKJA/UZppCib9fCiiXs1r4dJ5zQs0G/h+UL/2T6ysXktmrDoEF9YzbWD175ATZvpHev/Rh02B4xe51Upr+lNavPvBISM5ftt2eXOo0t1cRivpnQ4mvr1q1xOBxs3Lixytc3btxIfn7+Ts9fsWIFq1at4pRTTol+LRRZSMrpdLJs2TL23nvvKtukpaWRlpYWfVxUVASAy+WK2S93wAi3IXti+Bp15YpkXRo2u+Vj8YfC7zPD7UzI+4zlZyh106NjLgAbi7yU+g1yM8ILW20q3cTv2zaSAzxsW8fpRDJQuw3BdtrjOJxZsHhmgz9Djzv8pysYstW4fUFZOP6jTY7Hsp+T/NwMALaU+Krd54ai8O2kHfOymsXPpn4HU1+8P0OXy4XN5sBehzw9m80RHV9T364hmuvv3jXXXMNjjz3Go48+atk+4zEfhcTMSSX29PmlAMOA756FWbdA0As5u2Eb/hy29gfCzIbPRyUxApGbOdMqnYPW9zPM8oT/FpcHjJh+9t7IYLM8+hmrjX4Pd1afeSUkZi7rdKZUP2edxWK+mdD/U263m759+zJnzhxOP/10IDx5nTNnDmPGjNnp+d26deOnn6reYnzrrbdSXFzMI488wu677x6PYdeqYsGtxOdfuBzhMQRikF1UHgjngKQpQLzZyva42K1lOmu3l7F0QzGH7dWKz9d8ztmvnU3f4DU8kfYUu9l8YHfBif+CQy8Hm61e+a7VMRfc8u3i53priQ+A1pnuRr1WZW1zwkXkzdUsuGUYRnTBrQ65WnBLRCQWvvnmGz7++GPeffdd9ttvv51O1GbMmFHvfTbV+aiIAOWF8PbVsOTN8ON9T4bTn6j3egOSPHyRc+20Riy4ZS4Y7Y3TglsenS+LpJRYzDcTXqYeO3YsF154IQcddBCHHHIIDz/8MKWlpdHVZi+44AI6duzIxIkT8Xg89OxZ9Vbf3NxcgJ2+nkhmQcgsECWS0x4egz8WxVd/eJ86mDRv3fJzWLu9jF/WF/LZ+ucY99E4rjFc3OO+B5ctSDC3E44zp0LHAy17TVddiq+l4QJpq6y0Gp9TX22zw/vaVE3xtbDMH51gtctR8VVEJBZyc3MZOnSo5fttivNRkWbvz+/htZGwfRXYnXDCnXDYVeFGAElZXguKr+mR89eyOBVf03W+LJJSYjHfTHjx9eyzz2bz5s3cfvvtbNiwgd69ezNr1qzoogdr1qzBbk98EbM+/MlUfI10vvqD1i62BVBuXslrxIFPUl+3/Gw++mUjj30xg9U7buYNPJyCC2xB3gseysmXvQoZuZa+pjvyM2de+a7Olkjna6ssCztfI8XXbaU+fIFQdBxAtOu1VaZbFyRERGJk6tSpMdlvU5yPijRbhgFfPwUf3gohP+TuAcOnwW6xy/aU+KnofG34fNvjjk/xVc1KIqkpFvPNhBdfAcaMGVPtbV0Ac+fO3eW206ZNs35AjeSLZLu4kqAoaRaAA6FYdL5GruS5dTBpzpxp4Yy83Qr+4C13FrtjI+RI4/by83jbdRKDLS68Qt2Kr1tLIp2vmdZ1vrbMcOO02wiEDLaUeOmQmx793vrCMgDyW6jrVUQkFTW1+ahIs1S2Hd4aA0vfDT/uNgROmwTpuQkdlljHG4m+czcmdiBSuDWLo7Gi82URMSVF8bWpMW+FdjWbzlcdTJojwzB4/JvH+efcB7jdMZDrna/ixAZ5e7PsqEd54ZVCdsuxruu0MvN3a1dxGltLI5mvFna+2u022mSnsb6wnE3Ffy2+hjtf26v4KiISM507d8a2i1uGf//99ziORkSSytrvYPpIKFwDDjec+G84ZJRiBpoYKzJfzWJouS/GsQM+xQ6IpKJYzDdVfI0Bc8GtxlyNs4rT7HyNSfHVvI0i8e9T4quwvJBL37mUuYtf5zXSOdn1MgCl+55B5rDH2LCqDPiWFumxWbEyrZbOV38wRMGO8CIKVma+Qjh6YH1hOZuKyqt8fX2BWXxNr24zERGxwLXXXlvlsd/vZ+HChcyaNYsbb7wxMYMSkcQKheCrSfDRBAgFoGVnOHMqdOiT6JFJDJiZr42J+It35qtiB0RSSyzmmyq+xkBF5mvir7K67Gbna+xiB3QwaV4WbVjEmdPPpMPWlSwik47Y8eLmNv+FHNfrek5Ky6aorAggZsXXaOxADT/X2yNdr3Yb5Fo8hjbZHqBwp0W3zM5XxQ6IiMTONddcU+3XJ02axHfffRfn0YhIwu3YBm9cAb99EH683xlwyiPgaZHYcUnMRDtfG9EAZDYPBUIG/mAoZneslil2QCQlxWK+qZbFGEiu2IHI7dkxyHzVlbzmxTAMpiyYwuFTDuOcrWv4OFJ4pfW+PLb307waPJZlG0sAKCoLd53GrPjq2HXnq7nYVl5mGna7tRdB2uWEO2n/2vm6oSic+dohV8VXEZF4O/nkk3n99dcTPQwRiac1X8HkI8OFV0caDH4Qhk9V4bWJs6LztfL5a3mMul9DISN6rqIFqkWahsbMN9X5GgO+JIodcMUldkDF16auxFfCle9dyewfXuRt0hlg/uk44DwYfD+5X2+Exb+wdEO447UwUnzN8cSm+Gr+XPtq+LneWhruSrUy79XUNjtcXN2p8zUSO5Cfo9gBEamfUChEQUFBvbeRCq+99hp5eXmJHoaIxEMoBF88DB//C4wgtNoHzpwG+b0SPTKJA2+087Xh56BpTjs2GxhGuKEoOwbnLOWBiqKuOl9FmobGzDdVfI0BfxJ1vroi0QeBWMQOBMzO18S/T4mdJZuXMPzV4bTf/CuLyCQfO4YrA9vgB6D3eQB0y88BYOmGYqCi+NoiI8axA4Hqr1RvjXS+topF8dXsfK1UfDUMIxo7oM5XEamvgoICHnx3IZ7M7Do9v7y0mGG9mmehsU+fPlUWQDAMgw0bNrB582aeeOKJBI5MROKiZDO8cTmsmBN+3OssGPIgpNXt76ekPm9k/t+YzlebzUa6y8EOX5ByX2wuZpZVWsxLC1SLpJZYzDdVfI0BM3YgGTpfnXYzdsD6zlevYgeavBd+fIEr37mcG/xBbiMznFPStge24VOhbbfo87q1D094V20tpcwXrCi+xjrztcbYgXBhtFWmtYttQXjBLYBNxRWxA4Vl/mgMR7scFV+l6atvp2Zubi52e+KPicnMk5lNZk5uooeR9E4//fQqj+12O23atKF///5069at+o1EpGlY9Tm8dgmUbABnOgy6D/qcD7tYkVqaHisyXyF8DrvDF6zSoWol89wgzWm3PAZNRGIrFvNNFV9jwB8IFzobczXOKs5I56u/hiJVY5ixA+kqvjY5Zf4yrpl1De8ueIZ3SKc/kSLmgRfASfeCO6PK81tnpdE6y82WEh+/biymqCwAQI4nNn9izN8tf42xAzHsfDVjB4oqOl/NrtdWmW5djJBmoT6dmuWlxYwd0ke3hIslxo8fn+ghiEi8hYLw2QMwdyIYIWjdNRwz0K5HokcmCWBF5itUnMNW7lC1kiL6RFJXLOabKr7GQFLGDsSg87Viwa3Ev0+xzm9bf+PM6WfSbsPPLCKTttgx3FnYhjwM+59Z43bd8nP4fPkWlm4oqsh8TVDn69YSM/M1Bp2vkdiBLSVegiEDh93G+sLwYlv5LdT1Ks2HOjVFRCTmijfCjFGw8tPw494jYNB/wJ2Z2HFJwvgsyHyFinPYshgtuGUu5KVGJREBFV9jwpuEC275Y5H5at5KoQNKk/HaktcY9ebF3OTzMY7IpLZdL2xnToPW++xy22752ZHia3H8Ygdq+LmOZr5mWt/52irTjc0GISO8sFfbbE+087W9iq8iIjFht9urZG9Vx2azEQgE4jQiEYm53+fC66OgdBO4MmDwg9D73ESPShLMisxXqOhILY9R8dUs6mqxLZHUEcv5poqvMVDR+Zr4bBdn5KAUqOH27MYwD1QKEE99vqCPGz+8kRlfP8Y7pHOkGTNw0CUw8G5w1V5U7Jofvv146fpiispj3PnqqCXzNRo7YH3nq9Nhp1VmGltKvGwqihRfC8zia7rlryciIvDGG2/U+L358+fz6KOPEgrFZtEUEYmzYAA+vRfm/QcwoG0POPN5aLNvokcmScBsvmhs5mt6rIuvPq2PIpJqYjnfVPE1BqILbiVD7IDdjB2IYearrualtNUFqznrtbNovfZ7FpFJK+wYadnYTnkUeg6t8366t88BYOmGomjMRaw6X82O7po7XyMLbsUg8xXCi25tKfGyuTj8Ombnq2IHRERi47TTTtvpa8uWLeMf//gH77zzDiNGjODOO+9MwMhExFJF6+H1S2D1F+HHB14IJ98LLl3gljCv36LM18g5bKxiB6Kdr4roE0kZsZxv6i9BDPiTKHbAGS1SxbDzVQeUlPXur+9y8OTenLn2B94jg1bYoX1vbJfPq1fhFWCftlnYbbB9h5/i8nAbfsxjB2rMfA13vrbOtL7zFaBdJPd1Y1G46LqhKJz52iFXxVcRkVhbt24do0aNolevXgQCARYtWsTzzz/PnnvumeihiUhj/PYRTD4iXHh1Z8GwZ+HUR1V4lSrM5ovGnoOmOc3O19jcNVFxrqxGJZFUZPV8U1WzGDBXYE+qBbdimPmq2IHUEwgF+MdH/2DMS6fydrmPG8yYgUOvgEs+hLy96r1Pj8tB59ZVFz/I8cSm+Jq2i+LrDl8geqU5dp2v4SLrJrPzNRI7kJ+jkwMRkVgpLCzk5ptvZp999mHx4sXMmTOHd955h549eyZ6aCLSGMEAfDQBXhwGO7ZCfi+47FPoNTzRI5MkVNH52rhz0Gjnq08LbolIhVjNNxNfHWxiDMOIXo1LjuJrDDNfA+ZVRx1QUsmfRX9y3PPHsfTzB1hIFofhxPC0gLNfCN/W5Wx4t2i3SPQAhCcaser+3tVCcmbXq8dlJyNGkRhtI52vm4rLMQwjGjugzlcRkdi477772GuvvXj33Xf53//+x5dffslRRx2V6GGJSGMVroVpg+Hzh8KPD74ULvmo1oVepfmyLvM1vH3MYgfMzFdF9InU6J577sFms3HttddGv1ZeXs7o0aNp1aoVWVlZDBs2jI0bN1bZbs2aNQwePJiMjAzatm3LjTfeaMmiq7Gcbyrz1WL+SkXOpIgdiGS++i3OfPUHQwQjuZ66mpc6Zq+YzcjXz+OGHcVcS0b4ix37Yhs+FVo2/nbNbu2yeY/1QOwiB6DidysQMgiFDOz2isXttph5r5lpta5U2FBtsyPF1yIvhWX+6KStXY6KryIisfCPf/yD9PR09tlnH55//nmef/75ap83Y8aMOI9MRBps2Sx48woo2w5pOeGIgf3OSPSoJIkFKp2DNjbz1Wwg8sYs8zWyPorOlUWq9e233/LUU0+x//77V/n6ddddx3vvvcf06dNp0aIFY8aMYejQoXzxRTgLPBgMMnjwYPLz8/nyyy9Zv349F1xwAS6Xi7vvvrtRY4rlfFPFV4tV7sRLigW3YtT5WvkKYWOvOkrsBUNB7pp3F/839y7eJJ2DzJiBfmPg+PHgtOb2/Mqdr/EovkL46rfHXjGpiea9xihyAKBNpdgBs+u1VaZbXeAiIjFywQUXxOyCmojEWcAHc+6A+Y+HH3foA8OnQl7nxI5Lkl7lxXbD56ANP8c1i6KxX3BL5wcif1VSUsKIESOYMmUK//rXv6JfLyws5Nlnn+Wll17iuOOOA2Dq1Kl0796dr776isMOO4wPP/yQJUuW8NFHH9GuXTt69+7NXXfdxc0338yECRNwuxteB4jlfFPFV4tVzqBMis7XSOZrdbdnN4aZYWOzVeRvSnLaVLqJETNG0GLFXL4nkxbYMNJbYjv9Seh6sqWv1S0/O/rfOemx+/NS+cKGLxiqUvTcWhrpfM2KzWJbUBE7sLnYy/rC8GJb+S3U9SoiEivTpk1L9BBExArbV8NrF8Of34UfH3olnHBHo2KvpPnw+qs2OhmhhhdOPTEuvnq1OLU0I8XFxRQVFUUfp6WlkZZW89/10aNHM3jwYAYMGFCl+LpgwQL8fj8DBgyIfq1bt27ssccezJ8/n8MOO4z58+fTq1cv2rVrF33OwIEDufLKK1m8eDF9+vRp8PuI5XxTxVeLmUVOuw0c9sR3aDjtNWdjNoZ54Etz2tWJksQ+W/0ZF0w/ixtKChhtxgzsfii24c9Bi90sf73dWqaTleakxBuIaeeruZAc7Lzo1pZI52urzNh1vpqxA5uLvayLLLbVXsVXERERkZr98i68dRWUF4KnBZz2BHQfkuhRSQoxO18ddhtOhx2/BcXXcr/1C1ODOl+leenRo0eVx+PHj2fChAnVPvfll1/m+++/59tvv93pexs2bMDtdpObm1vl6+3atWPDhg3R51QuvJrfN7+XrHQZxmLJtNgWgNsZLlIFQtbGDmj1xuQWMkLc+/m9jJp2HDNKihlNpBB55HVw0XsxKbwC2Gw2uka6X3NiWHy12WzR7te/Fl/N2IFYdr62iRRffcEQSzeEr/C1b5Ees9cTEbFSLBc3mDt3LgceeCBpaWnss88+6lgVEQh44f2b4ZUR4cJrx4Pgis9VeJV6MxuArIj304JbItZZsmTAtNquAABoUUlEQVQJhYWF0X/jxo2r9nl//PEH11xzDS+++CIeT/NqXkqOCmETYhaCkiFyACo6X2OV+aqMy+SzrWwbp718Gos+upVvjXT64MBIz4MRr8OACeCIXVEUKqIHctNj13kKFb9jOxVfI7EDscx8TXM6yM0I/3/84Y9CQLEDIpIadrW4wTvvvMP06dP59NNPWbduHUOHDo1+31zcwOfz8eWXX/L8888zbdo0br/99uhzVq5cyeDBgzn22GNZtGgR1157LZdeeikffPBB3N6fiCSZbb/DsyfC15PDjw//O1w8C3L3SOy4JCX5guFzUCvWHEmPFEXLfcp8FWms7OxscnJyov9qihxYsGABmzZt4sADD8TpdOJ0Ovn000959NFHcTqdtGvXDp/PR0FBQZXtNm7cSH5+PgD5+fk7NQiYj83nJKPkqBA2If6gNasvWiV2ma/h/an4mly+Xvs1h03uzanLPuJ/ZJCNDWPPw7Fd+QV0GVD7Dixw0eGdOLlnPmcdHJvuWpOrhp/tis7X2BZ/20UW3fplfbjztUOuiq8iktwqL27QsmXL6NfNxQ0efPBBjjvuOPr27cvUqVP58ssv+eqrrwCiixu88MIL9O7dm5NPPpm77rqLSZMm4fOF/+5OnjyZzp0788ADD9C9e3fGjBnD8OHDeeihhxLyfkUkwRa/AU8dA+sXQXpLOO9VOPFfMW8EkKar3MLO12jsQCA2xVedL4vs7Pjjj+enn35i0aJF0X8HHXQQI0aMiP63y+Vizpw50W2WLVvGmjVr6NevHwD9+vXjp59+YtOmTdHnzJ49m5ycnJ3iD5JJclQImxB/ksUOmOOI1YJbWmwrORiGwaNfP8qo547m9cJtjMKNgQ2OvgnbBe9AToe4jaVLu2ye/FtfuuXnxPR1zM5X706Zr5EFtzJju3CDueiWGemRn6PYARGJP3OBA/Of1+ut8bmVFzeorLbFDYAaFzcoKipi8eLF0ef8dd8DBw6M7kNEmgl/Obw7FqZfBN4i2P2wcMzAvgMTPTJJcWbEnxWdr9EFt2LU+aqYPpGdZWdn07Nnzyr/MjMzadWqFT179qRFixZccskljB07lk8++YQFCxYwcuRI+vXrx2GHHQbAiSeeSI8ePTj//PP54Ycf+OCDD7j11lsZPXr0Lhf5SjQtuGUxb9LFDkQyXy2OHYgeTJRhk3CF5YVc8vYlZCx5m/l4yMRGKLMN9qFTYO9jEz28mInGDvy187U0Pp2vZu6rSZ2vIpIIdV3gIB6LG9T0nKKiIsrKykhP10UqkSZvy/Jw0XXjT+HHR46FY/8JDp12SuNZm/kaKb7GeMEtdb6K1M9DDz2E3W5n2LBheL1eBg4cyBNPPBH9vsPh4N133+XKK6+kX79+ZGZmcuGFF3LnnXcmcNS101HQYhWdr7Zanhkf0c7XkLUHlejBxKmDSSItXL+QC14dztjt6xhJ+KTW6Hw09qHPQHa7WrZObdGf7Uqdr6GQwbZI8bV1DBfcAmibXbXY2i5HxVcRib8lS5bQsWPH6OPqrvibixvMnj272S1uICJx9ON0ePda8JVARmsY+hTsE5/YK2keop2vFpyDmkVRb4wX3FKzkoRCoZ0yTGvz1wviTdncuXOrPPZ4PEyaNIlJkybVuM2ee+7JzJkzYzwya6n4ajFz8Z9kix2wuvPVG82wSY732dwYhsGU76cweeY1vBJ00AM3hs2Orf84bEddD/amf5A3r3hX7nwtLPMTjMQAtMyIbedr20qdr60y3bqqLSIJYS5wsCuVFzcwBYNB5s2bx+OPP84HH3wQXdyg8mT/r4sbfPPNN1X2+9fFDWpaACEnJ0ddryJNmW8HzLoZvv9v+PGeR8KwZyCnfWLHJU2OWSi14i7Tis5XxQ5IbBUUFPDguwvxZGbX6fnlpcWMHdInxqOSeFPx1WL+6NW45ChKmgtuBUIGhmFgs1nTkWsGk6vgFH8lvhKueOdy0n6azud4yMBGKKst9mHPQeejEj28uDF/x3yVOl+3loazDluku2Ie/WFmvgLkt1AnmYgkL3Nxg8pGjhxJt27duPnmm9l9992jixsMGzYMqH5xg3//+99s2rSJtm3bAjsvbtCvX7+duhBmz54d3YeINEGbl4VjBjYtAWxwzE1w9E2KGZCY8Fl4rp3uDu8j1sVXNSsJgCczm8yc3EQPQxJIR0WLJd2CW/aKcfiDBm6nRcVXXclLiMWbFnPhK8O4dutq/mbGDOx9HPYznoasNgkeXXy5qym+bimJT94rVI0daK/iq4gkMXNxg8oqL24ARBc3yMvLIycnh7///e81Lm5w3333sWHDhp0WN7jiiit4/PHHuemmm7j44ov5+OOPefXVV3nvvffi+4ZFJD4WvQTvXQ/+HZDZFoZNgb36J3pU0oRFM18tKL6a0QXlsYod0PmyiFSi4qvFvEkWO+CslD0bCIVwY824ynzmSpM6mMTL//3wf0x65wpeDNjoasYMHHcbtiOuBXty/LzFk6ua2IGtkeJr68zYr3JYOXagfQvdTisiqc2KxQ06d+7Me++9x3XXXccjjzzCbrvtxjPPPMPAgVrhXKRJ8ZXCezfADy+FH3c+BoZOafLrDUjiWZn5amaxlvtDhEIGdru1a7ZowS0RqUzFV4v5I9mqsb7lua4qF4H9Fua+VsQOJMf7bMrK/GVcPfPvOBb+l7l48GAjmJ2PY/g02LP53spZXeerGTsQl85XxQ6ISAqL1eIG/fv3Z+HChVYMUUSS0cYlMP1C2PIr2OzQ/xY4amyzWG9AEs/MfLUkdqBSUdQbCFm6MFYoZFAe6dLVglsiAiq+Wi7pYgcqd75W6hBsrHJdyYuL37b+xoWvDOWaTSs424wZ6HIijjOegoy8BI8usapbcCuesQMZbifZaU6KvQE65Kr4KqkpFAqxbdu2Oj8/NzcXezPstBcRafYMI7yg1vs3QaAcstuHF9XqdGSiRybNiJWZr5XPY8v9QUuLpN5KzSGKHRARUPHVcmYXXrIsuGWz2XDYbQRDBoGQhZ2v5pU8HUxiZvri6Tz25iX812+wDy5CNgf2E+7AdtjoZhkz8FeuyO+Yv3Lna0mk8zUOsQMAu+dlsGR9EXu2yozL64lYraCggMc++LlOq6+aK6/m5TXvCz8iIs2OtxjevQ5+mh5+vM8AOOMpyGyd2HFJs2Nl5qvDbsPtsOMLhijzB2nZ6D1WqJwjq2YlEQEVXy1X0flqbWZMYzgjxdfKt2c3llZvjB1vwMsNH1wP3z7NbDykYSeQ0wHnmf+F3Q9O9PCSRtquMl/j0PkKcN/w/flxbSF9ds+Ny+uJxIJWXxURkRqt/xFeGwlbl4PNAcffBodfo0YASQgrO18hfC5rFl+tZO7P7bDjsDhLVkRSk4qvFvMlWewAhMfiDYQs7nxV7EAsrCpYxSWvDGP0+l8YGokZCHUdhPP0JyDdyuuxqW/Xma/x6Xzt2bEFPTu2iMtriYiIiMSNYcB3z8KsWyDohZyOMPw52OOwRI9MmjHzdn6r1ldJdzsoKg9U6VS1QpkalUTkL1R8tZjP4gOCFcwu3Jhkvlqw0qSEvb3sbR6ZcQHPeIN0xkXI7sB+4t3YD70cbLpi+lfR4mulheTMztdWmfHpfBURERFpcsoL4Z1rYPEb4cf7ngSnP9ns1xuQxKuI+LPmHNRsJLK8+OoL70+LbYmIScVXiyXbglsAzshY/EHrM189OqA0mj/o559zbiHw5aPMIg0XdvwtdsN11v9BxwMTPbykZf6OVe583VIS385XERERkSZl3UKYfhFsXwV2Jwy4A/qNViOAJAVvIHI7v1Wdr5Hia5nPuiYlqBin7hIVEZOKrxYzC5xJ1fkayZkJhKw7qERvpUii95mK1hatZdQrw7nyzx85FQ8Aoe6n4DptEnh0O/uu/DV2wBcIUVQeAOKX+SoiIiLSJBgGfPM0fHgrBH3QYg84cyrsdlCiRyYS5bV4cWuzOGp55qtPi1OLSFUqvlosGjuQlJ2vsVhwSweUhvpwxYc8PP1cnir3sQcugnYnjpPvxX7QJeouqAN3dMGt8M/ittJw5IDTbiPH40rYuERERERSStl2eGsMLH03/LjbEDjtca03IEnH6sxXM5M1dpmvOlcWkTAVXy2WjAtuOSOZr1bGDpgHPh1Q6i8YCnLn3Al45/2Ht3HjxI4vdw/cZ78I7fdP9PBShjnp8gfCP9dm5EBephu7VhUVERERqd3a7+C1kVCwBhxuOPFfcMhlagSQpGR15mt6rDpfI/tT56uImFR8tZh5QHA5k2fCYnYIBizNfNUBpSE2lmzkyulncunq7xhEOJc0uN8ZuE99DNKyEzy61FLR+Rr+ndsa6XxV3quIiIhILQwD5j8OH02AUABadoIzp0GHPgkemEjNrO58NRfEsrrztVwLbonIX6j4ajHz1v7kih2IdL7GIvPVlTzvM9l9uupTHn7lTB4vK6MjLgJ2F87BD+A48AJ1FzTAXzNft0Y6X5X3KiIiIrILO7bBm1fCr7PCj3ucDqc+qvUGJOn5IgtZWZb56oxR8TWgc2URqUrFV4tFi69JtBCV0x67zlfFDtQuZIS477OJlH5yF68ZbhzY8bbsRNo5L0G7/RI9vJQVLb6ana8lkc7XTBVfRURERKq15it47RIoWguONDhpIhx0sRoBJCVYnvka6Uw1F8iySplP58oiUpWKrxaLxg4kUeerK5r5as1BxTAMyv2RvB1dzdulrTu28vfpZzNy5XxOiMQM+HudSdqQhyEtK7GDS3Hm75j5O7elNNz5qtgBERERkb8IheCLh+Hjf4ERhLy9wzEDWm9AUkhF5qtFsQPKfBWROFHx1WK+SHdpUsUORDpfrSq+mlccQQeUXZn/x3weeXkYD5cWk48Tv8ONc8hDuPr8LdFDaxJ2jh0wM1/V+SoiIiISVboF3rgcln8UftzrTBjykNYbkJRjeedrpJHI6tgBFV9F5K9UfLWYP7rgVvIUX82xWBU7UPngpFspdmYYBo/Mf5Di2bfxkuHEjp3ylp3xnPsytO2W6OE1GTstuGVmvmaq81VEREQEgFVfwOuXQPF6cHpg0H+gz/mKGZCUVNH5as05qFkc1YJbIhJrKr5azJeEC2657OHJVcCiBbfMyAGH3ZZU8QrJoKC8gOtfG8Hfls/lWFwA+A44B8/gh8CdkeDRNS1uZ9U4ja2l6nwVERERASAUhM8ehLl3gxGC1vvCmc9Dux6JHplIg3mtXnArRrED5vmyGpVExKTiq8UqFtxKnqvJzmjmq7Wdr54k6u5NBgvWLeCRl07j/pJC2poxA6c+jvuAsxM9tCbJ7QhPZnaOHVDnq4iIiDRjJZvg9Uth5afhxwecB4PvB3dmYscl0khWZ756YtT5WqbFqUXkL1R8tVgyLrjldFib+Voe0G0UlRmGwdPfPkHB+zfxX8MJ2NnRam8yzn0VWu+T6OE1WZUzXw3DYEskdqBVpjpfRUREpJn6fS68PgpKN4ErAwY/AL3PS/SoRCxhdeZrxYJb1pwnm5T5KiJ/peKrxZI6dsCiztcyn3m7hw4mxd5ixr1xAWcv/ZCjIr9O3t4jyBj8ALjSEzy6pi1afA2GKPUFo5MxxQ6IiIhIsxMKwqf3wqf3AQa07QFnToM2XRM9MhHLWJ75GmkmMjNarWJ20qa7k6cmICKJpeKrxczu0qRacMvsfLU489VcHbK5+mnjTzz24incXbSV1jjxOty4z3iKtJ5DEz20ZsEVidPwBULRxbYy3A4y3PqzJiIiIs1I0XqYMQpWfRZ+fOAFcNK9Wm9AmpRgyCAQCjcTWdX5ap7Pmnd2WqVcna8i8heqUljMvBqXTJ2vZuyAVZ2v5sGpOWfYPP/9s2x99xqeDjkAOyWt9iFrxHTI2yvRQ2s20ip1vm4p0WJbIiIi0gwt/whmXA47toA7C4Y8DPufmehRiVjOPM+GGCy4ZXHnqxk7kNaMz5dFpCoVXy1mLmpl1dU4K5gdggGLMl+9zfhK3g7/Dsa/OZKhi9+lX+TXZ8eBF5A16H5waqGneKq84NbWaN6rPgMRERFpBoIB+ORf8PlD4cfteoVjBrTegDRR3krdqdZnvlpcfPU13/NlEameiq8W8yfjglt2s0PQoszXZrp647Ity5j0f4O5o3ATLXFS7kzDPXQKGT1OS/TQmiWXM3xRwR8MsbU03PnaWp2vIiIi0tQVroXXLoE/vgo/PugSGHg3uDyJHZdIDJmdr3YbOCNrmjSWeT5bbvGCW+b+VHwVEZOKrxbzmpmvDmsOCFawuvO1OWa+vvrjC2x+6yoeDdoAG4Wtu9BixGvQslOih9ZsmdEe/qDB5mJ1voqIiEgz8OsH8MblULYd0nLglEdA6w1IM2Aurut22rHZrDnXTo8WX2MTO2Au6CUiouKrhQzDiC64lVyxA5HM15BFma/NKMPGG/Dyr7cu5dSf3uAswu+3pO9FtDj5P+BUl2UiVf4dW19YDijzVURERJqooB/m3AFfPhZ+3L43nDlV6w1Is2EWX9Oc1p2DmsVRq2MHzPNlj4VjFZHUpuKrhYIhAyNS30yuBbcqbs+2QnO5jeL37b/z1H9P5pbt62mBgx3ONNKGPUdW9yGJHppQtfi6obAMgFZZ6nwVERGRJqZgDUwfCX9+F3586BVwwp1ab0CaFTPz1comJ7M4GgyFm6isiA40DKMips+dPDUBEUksFV8t5KtU3EymzNdo56vlma/J8x6t9vbiV9k4YxT3BgFsbG+9Ly3/NgNyd0/00CTCZd+581WZryIiItKk/PIuvHUVlBeCpwWcNgm6n5LoUYnEnS/a+Wph8bVScbTMH7TkHN4bCEUbspp6s5KI1J2KrxbyByqKm8kUO2AGklvV+eptwrdR+IN+7n/nSgYueplTIzEDRQddQsuT7wWHK8Gjk8rsdhsuhw1/0GBdQaTzVZmvIiIi0hQEfDD7dvj6yfDjjn1h+FRouWdixyWSIJUzX63idtix2yBkQLkvSI6n8ed7lfNjm9sC1SJSMxVfLVS589WqFRit4DQXJrI487WpHUz+KPyDKf89iRu3/kE2DkqcHtLOnEpO10GJHprUwO2w4w8GKSoPAMp8FRERkSZg20p4bSSsWxh+3G8MHD9e6w1Is+aLQearzWYj3eWg1BeMRus1lnmXqMthS6q7YUUksVR8tZAvaP0KjFZwRzJfA1Znvjah1Rs/+OUtNrx+EXcGQoCNLW32pfX5b0FOh0QPTXbB5bSDr+LqsoqvIiIiktIWvwlv/x28RZDeEk6fDF1PSvSoRBIuFp2vEG4oKvUFLVt0yzxXbop3iYpIw6n4aiG/eUBIsitc0c5XizNfrczbSZRAKMDjM6/muO/+y0AchICCgy+l9Un3gkO/Hsnur79reRkqvoqIiEgK8pfDh/+Eb58JP979MBj+LLTYLbHjEkkSsch8hYq7Oa0qvpb5zMW2VHwVkQqqLlnIzFR1OZKn6xUqIhACIas6X5tG7MD64vVMe34gV29ZRSYOipwePGf9l7x9ByZ6aFJHla98t8xwRS80iIiIiKSMrStg+oWw4afw4yOvg2P/qfUGRCrxBmLTAGTezVluVfE1sh8ttiUilan4aqFY3QrRWK5o56tFxdfI+0zl4uunv77P+ldHMC4QBGxsaNOV/Avehuz8RA9N6qHy71qrLC22JSIiIinmp9fgnWvAVwIZreCMp6HLgESPSiTpxK7zNbw/62IHVHwVkZ2p+Gqhis7X5Cq+OiOduFbFDqTyASVkhHj6/bEc9c0zHIODILDtkFHkn3Qv2FPv/TR3lWMHWmUqckBERERShL8M3r8Zvn8+/HjPI2DYM1pvQKQGsWp0Ms9py33WFl8VOyAilan4aiFfkma+msVg6xbcMmMHkut91mZL6Wb++/xArti0nAwcbHd6SD/nRdrso+6CVFV58tVana8iIiKSCjb/Go4Z2LQEsMHRN8IxN2u9AZFdqOh8tbaoaXnmq3munGR3w4pIYukIbyGzszT5YgfMzFdrO19TKXbgq9/nsO5/ZzPW7wds/NmmKx0vfA+y2iR6aNIIVTpfs9T5KiIiIklu0f/gvbHg3wGZbWHo07D3sYkelUjSMzNfrW50Ms9py/3WNCqZC26lq/NVRCpR8dVCSRs7YDczX60qvpqZr8n1PqtjGAb/9+FNHDp/ModhJwBsOfRyOg68B+zJP37ZNVeV2AF1vkrzFQqFKCgoqPPzMzMzYzcYERHZma8UZt4Ii14MP+58NAx9BrLbJXZcIiki2vlq8TlousWdr6kc0ScisaPiq4XMHBqz0zRZVGS+Wh07kNwHlIKy7bw07UQu3rgMD3a2Oj2kn/MS+fscn+ihiUWqLrilzldpvgoKCnjw3YV4MrNrfW55aTF/H9gzDqMSEREANv0C0y+CzUvBZof+4+Co67XegEg9eGMU8RfNfLU4dkDFVxGpTMVXC5nFzeSLHbA287UsBYqvC1fNY+2Lw7jK7wNsrG7TlT0umokts3WihyYWqpr5quKrNG+ezGwyc3ITPQwRETEZBiz8P5h5EwTKICs/vKhW56MSPTKRlOONUeereTenVcVX8y7RtCQ+VxaR+FPx1ULJGjtgjseq2AFvNHYg+Q4ohmEwfc6t9P38UU7Bjh/YeOjl7KmYgSapauarYgdEREQkSXiL4d2x8NOr4cd7Hw9nPKX1BkQaqKLz1eIFtyLZrGZWa2Op81VEqqPiq4V8MboVorGcdnPBrcZ3vgZDBr5IkTnZVnAsLi/itecHct76xaRhZ5MzjfRz/8dueytmoKmqEjuQqc5XERERSQIbfgrHDGxdDjYHHHcrHHGtGgFEGiFVMl8rFtzS77uIVFDx1ULJHzvQ+M5Xc5VJSK4VHBev+ZK1L5zOSJ8XsLG8bVf2vmgWtoy8RA9NYkidryIiIpI0DAO+ew5mjYOgF3I6wrBnYc9+iR6ZSMozz0OtbnTyRDNfrV0fRZ2vTU99F7gFyM3NjclYJPWo+GohX6S4mWyxA+aCWz4LMl8r347hcSbHAeWdjyfQa96DDMSGD/jz0CvY56R7wJZcC5+J9cwLHS6HjRyP/pyJiIhIgpQXwTtXw+I3wo+7DIQzJoMaAUQsEevOV6sX3ErGiD5pnPoscAvhRW7HDukT41FJqkiKKuGkSZPo1KkTHo+HQw89lG+++abG506ZMoWjjjqKli1b0rJlSwYMGLDL58dTNHYg2Tpf7dZ1vpZXilaw2xNb3NzhK+V/U45k4LwH6YSN9c40dpz/Bp1PvleF12bCvNDRKjMNmz5zERFphKYyH5UEWLcQnjo6XHi1O+HEf8G5L6vwKmIhb4wi/qyOHShX8bVJMxe4rcu/uhZppXlIeJXwlVdeYezYsYwfP57vv/+eAw44gIEDB7Jp06Zqnz937lzOPfdcPvnkE+bPn8/uu+/OiSeeyJ9//hnnke8saRfcclqX+WoeTKy+4lhfm0t/5ftHunLunz/hxsbSNl1pd/0ycvc+LqHjkvgyL3S0ylLeq4iINFxTmo9KHBkG9m+nwLMnwvaV0GIPGDkLDv+78l1FLFbR+WptUdM8r7Wu8zU8TsUOiEhlCZ8VPPjgg4waNYqRI0fSo0cPJk+eTEZGBs8991y1z3/xxRe56qqr6N27N926deOZZ54hFAoxZ86cOI98Z9HMV0dydeA5I5M/f9DAMBrX/ZoMGTZz5t3NwF/v4lhfOV7g18Mup9tVX2NPb5mwMUliVBRflfcqIiIN15TmoxIn5YUcvPIxHB+Og6APug2BK+bB7gcnemQiTVKsMl8t73yNLril4quIVEhoSKLP52PBggWMGzcu+jW73c6AAQOYP39+nfaxY8cO/H4/eXnV39bj9Xrxer3Rx8XFxQD4/X78fn8jRr+zMl8AAKcdy/fdKKGKA0m514ezEQeskjIfAGlOe9zfY7l/Bx++cAqnrVuEExtrnW6cZ75I572OxR8IxHUs0jjmz05jf4bMRURbZTiT63euibPq8xPr+P1+DCNIKFT7iYNhBKt8hvXdzvyn7RKznbltIJBcF3pTWTzmoxDfOanElu3P73G8cQkdCv/AsLsIDbiD0EGjwrFX+ixThuYzqcUsvjptoZ0+u8Z8huYNnWXegCU/CzsiNQGX3dDPVh2k0u9hQ+Zr5vuK53bxnMtqPlp3CS2+btmyhWAwSLt27ap8vV27dixdurRO+7j55pvp0KEDAwYMqPb7EydO5I477tjp6/PmzWPJkiX1H/Qu/LbSDthZvWolM2eusHTfjVEeBPOjfnfmLBpzEW5ZoQ1w4C/fwcyZM60YXp0UlC5nz+UTGRbyAza+8OSztcvtGEvLYGn8xiHWmj17dqO2zyiHPq3sdA78wcyZf1g0Kqmrxn5+Yp3i4mJW/GmvU7ZUeWkxc8tXkJ2dzdy5c+u13ezIdvV9PW1n3XbmtvPXbanTc6V28ZiPQnznpBIjhsHem2fR489XsROk1N2W7zpfRcHm3eD99xM9OmkgzWdSw9btDsDGwgXfUbq86t2cjfkMVxQBONlaWGzJ+e2WyDh/WPAdO5Y3fs2V5iIVfg8bMl+bXR6uC8Vzu3jOZTUfrbuUXh78nnvu4eWXX2bu3Ll4PJ5qnzNu3DjGjh0bffznn3/So0cPjj76aDp16mTpeL56ewlsWEv3ffdh0HH7WLrvxvD6g9z8Tfg2uONPOIFsj6vB+/Is2wxLFtImrwWDBh1m1RB36fPP7+PghffRASgDlvUdyZZgf0448URcroa/F0kcv9/P7NmzOeGEExr9GZ5v0Zik7qz8/MQa27ZtY+Vnv5ORnVvrc3cUF9D/sN1ZsGAB/fv3Z+VXf9R5uxOO2ou8vLx6v562s247c9t+e3ap03Ml9uoyH4X4zkklBsq243hnDPY/PwAg0HUIc9OGcOxJp+lYmKI0n0ktDyz7DMrKOPqIfhy4Ry5gzWe4eF0Rjy7+Crvbw6BBxzR6nP/5ZR6UlXPMkf3ovXtuo/fX1KXS72FD5msnHLUXQFy3i+dcVvPRukto8bV169Y4HA42btxY5esbN24kPz9/l9vef//93HPPPXz00Ufsv//+NT4vLS2NtLSKPMiioiIAXC6X5b/cwciFLY/b+n03ht1R6WO2Oxs1tkAo3Fae7m7cfurCFyjno+cHMfCP73BgY7UzDc+5/2O/PY5m9cyZMfkMJb70GaY2fX7Jw+VyYbM5sNtrv7XBZnNEP7eGbGf+03aJ2c7c1ulM6evnSSUe81GI75xULLbma3jtYihaC440OOlujAMuIPD++/r8mgB9hqnBFwifbGekuXf6vBrzGWalh/8ul/tDlvwclEcWBsvOSNPPVT2kwu9hQ+Zr5nuK53bxnMtqPlp3CV1wy+1207dv3yqLE5iLFfTr16/G7e677z7uuusuZs2axUEHHRSPodaJP1J9tToEvLEcdhv2SBRHILIoWEOZQeSeGC+4tXbd9yz8z14M+mMBDmwsaNOFDtcvo93ex8f0dUVERKR5aWrzUbFQKASfPwxTTw4XXvP2hks/goMvDee7ikjc+CLnsWkua8+1PZH9lVu04FaZueBWAheoFpHkk/Ay9dixY7nwwgs56KCDOOSQQ3j44YcpLS1l5MiRAFxwwQV07NiRiRMnAnDvvfdy++2389JLL9GpUyc2bNgAQFZWFllZWQl7HwC+yFUulyP5JmNOhx1fIIQ/1LjcGfOg5HHGrsD89Wf3seecf3MosANYdugo+p58f8xeT0RERJq3pjQfFYuUboE3roDlkRzCnsPhlIchrW7ZeyJiLW/kPNTqRiezSOoNhAiFDOz2hp/LG4YRbVZS8VVEKkt48fXss89m8+bN3H777WzYsIHevXsza9as6KIHa9aswW6v+AP75JNP4vP5GD58eJX9jB8/ngkTJsRz6Dsxr8a5ncn3h9Zlt+ED/IHGdb6Wx7DzNRDw8ul/B3Psmm+wY2OF043n3Jfpo25XERERiaGmNB8VC6z6Al6/BIrXg9MDJ98HB16gbleRBIpV52t6pdWoywNBMtwNL5H4gwZmr1Oaiq8iUknCi68AY8aMYcyYMdV+b+7cuVUer1q1KvYDaiB/MLk7XyFIINS44qs3Ury1+krexvU/sO75QRxfXgLYmN96Hw685CPS0lta+joiIiIi1Wkq81FphFAQPnsQ5t4NRgha7wtnToN2+yV6ZCLNWihkxCziz1OpcarcHyLD3fB9lVWKLlDnq4hUlhTF16bCjB1wx/CW/IZyRQ5S5kGrocwMG4+FVxwXff4gu825gz4GlGDw8yGX0m/Qg5btX0RERERkl0o2wYxR8Pvc8OMDzoVB90OaYiREEs1Xad0SqztK7XYbbmc4oq+skbmv5l2iDrstKRuyRCRxkq9KmMLMztdkW3ALKrpxA40svloZOxAMePls6ons/9EEWhuwzOli899e4zAVXkVEREQkXn7/FCYfGS68ujLgtCfgjMkqvIokCa+/ovgai3Nts0vVbDRqqMqLbdkUUyKyk4kTJ3LwwQeTnZ1N27ZtOf3001m2bFmV55SXlzN69GhatWpFVlYWw4YNY+PGjVWes2bNGgYPHkxGRgZt27blxhtvJBAIxPOt1FvyVQlTmC9S2HQlYfHVGSm++hsZO1AeCB9QGnvFceuGH1ly/94ctfpr7NiY23ov9hj7K533ObFR+xURERERqZNQED65G/57GpRshDbdYdQn0GdEokcmIpV4g+FzUJstNhF/ZvG1vJGdr2UxXB9FpCn49NNPGT16NF999RWzZ8/G7/dz4oknUlpaGn3OddddxzvvvMP06dP59NNPWbduHUOHDo1+PxgMMnjwYHw+H19++SXPP/8806ZN4/bbb0/EW6ozxQ5YKKljByKLRDR+wa3GZ74u/uIh2n90B70MgyIMFh40kv5DHmnUuERERERE6qxofThmYNVn4cd9zg8vrOXOSOy4RGQnZuer22GPSUepGanX2OJrxV2iyVcPEEkGs2bNqvJ42rRptG3blgULFnD00UdTWFjIs88+y0svvcRxxx0HwNSpU+nevTtfffUVhx12GB9++CFLlizho48+ol27dvTu3Zu77rqLm2++mQkTJuB2NyK4OYb0V8FCFQtuJd//VrPzNRBqZOZrIw4ooYCXb6aexH6zJ5BnGCx2utgw4lWOUeFVREQkpuJ5m9fcuXM58MADSUtLY5999mHatGmxfnsi9bN8TjhmYNVn4MqEoVPgtMdVeBVJUmbma1qMmpzMTtXGZr6a22uxLWluiouLKSoqiv7zer112q6wsBCAvLw8ABYsWIDf72fAgAHR53Tr1o099tiD+fPnAzB//nx69epFu3btos8ZOHAgRUVFLF682Kq3ZLnkqxKmsGjmqzP58l0qFtxqXOert4G3UhRs/Ill9+/DIavDvzAftOrEnmOXsW+Xkxo1HhEREaldvG7zWrlyJYMHD+bYY49l0aJFXHvttVx66aV88MEHcX2/ItUKBmDOnfDCMNixBdr1gsvnwf5nJXpkIrIL0c5XZ2yKmuluM3agsXeJBqvsT6S56NGjBy1atIj+mzhxYq3bhEIhrr32Wo444gh69uwJwIYNG3C73eTm5lZ5brt27diwYUP0OZULr+b3ze8lK8UOWCgaO+BIvj+2zkjxtfELboXfY306X3/78hHazB5Pd8OgAINv+l7AiUMeUwi5iIhInMTrNq/JkyfTuXNnHnjgAQC6d+/O559/zkMPPcTAgQPj/r5Fogr/hNcvgTXhRgAOuhgGTgSXJ7HjEpFaxbzz1WlR56vPPFdOvnqASCwtWbKEjh07Rh+npaXVus3o0aP5+eef+fzzz2M5tKShzlcLRWMHkrHz1W7GDlh0Na8OBxQj4GXhtJPp8uHt5BoGPzicrD33f5x4yuMqvIqIiFgg2W7zmj9/fpV9mM8x9yGSEL9+GI4ZWDMf3NkwfCoMeUiFV5EUYd59Gavia7Tz1WdN5qtiB6S5yc7OJicnJ/qvtuLrmDFjePfdd/nkk0/Ybbfdol/Pz8/H5/NRUFBQ5fkbN24kPz8/+py/xmKZj83nJCMVXy3kDSR/5quvkZ2v5tXAtFoOKMUbf2bFA/vQZ9WXALydtzudxi6lZ9fBjXp9ERERqZBst3nV9JyioiLKysoa9B5FGizohw9vg5fOhLJt0P4AuGIe9Bxa+7YikjR8wdgubG0WS8sD1mS+asEtkeoZhsGYMWN44403+Pjjj+ncuXOV7/ft2xeXy8WcOXOiX1u2bBlr1qyhX79+APTr14+ffvqJTZs2RZ8ze/ZscnJy6NGjR3zeSAModsBC0czXJCy+uqKxA9Z0vnp2kbez6stHyJs9nn0Mg20YfH7gCE455Ql1u4qIiFhMt3mJ1KBgDbx2Maz9Nvz4kMvhxLvAWfvviIgkFzPzNVadr2mRYmmZOl9FYmr06NG89NJLvPXWW2RnZ0cv3rdo0YL09HRatGjBJZdcwtixY8nLyyMnJ4e///3v9OvXj8MOOwyAE088kR49enD++edz3333sWHDBm699VZGjx5dp3lwoqj4aiF/pKs0VlfkGsMVh8xXw1/GkheHsd+qLwD4zuHAfuY0Tu12aqNeU0RERKpn3uZVV+ZtXvPmzavxNq/K3a9/vc3rm2++qbK/v97mVdOtYDk5OaSnp9frvYk02NL34M2roLwA0lrAaY9DD81HRVJVReZrjBbcclmV+aoFt0R25cknnwSgf//+Vb4+depULrroIgAeeugh7HY7w4YNw+v1MnDgQJ544onocx0OB++++y5XXnkl/fr1IzMzkwsvvJA777wzXm+jQVR8tUgwZBAMhQubSRk7EMl89Tcy89UbqP6AsmPDz2x6fhD7lYUz5F5r2ZFjL/6YVtnJm7khIpJMQqHQTvlGtcnNzcVuT75jjiQfwzD4+9//zhtvvMHcuXN3eZvXsGHDgOpv8/r3v//Npk2baNu2LbDzbV79+vVj5syZVfY9e/bs6D5EYirgg9m3w9fhkzs69oXhz0HLTgkdlog0jnkOGuvYgUYXX6OxAyq+ilTHMGpvBvR4PEyaNIlJkybV+Jw999xzp/lmslPx1SL+SrfzN+XOV/NqXuXYgbVfPkLu7PF0Mgy2YPBJ77MZdtpT2G3J9/9BRCRZFRQU8OC7C/FkZtfp+eWlxYwd0ie6YJLIrsTrNq8rrriCxx9/nJtuuomLL76Yjz/+mFdffZX33nsvYe9dmoltK+G1kbBuYfhxvzFw/HhwuhM7LhFpNF8gtrEDZrHUjDdoqIq7RFV8FZGqVHy1iK9S8dXlSL5sU3PBLX9jM18DlQ4o/jJ+e3EYXSIxA1857DDsWc7soUUMREQawpOZTWZObqKHIU1QvG7z6ty5M++99x7XXXcdjzzyCLvtthvPPPMMAwcOjPl7lGZsyVvw1hjwFoEnF86YDF1PTvSoRMQi5sLWMet8jdzV2djM1zJlvopIDVR8tYh5NQ6Sc8EtZ+S2VH8jOl/9wVA0WsG+7Rf+mHwaXcoKCWHwv9wODLh4Du1yOtayFxEREYm3eN7m1b9/fxYuXFjvMYrUm78cPrwVvp0Sfrz7oTDsWcjdPbHjEhFLxavztbGxA1pwS0RqouKrRcyOUpfDhs2WfJ2vbmd4TIFGdL6aB5PT7Z+T9d8naWsYbCTEB/sPZ8Tpz+Cw6yAjIiIiInGwdQVMvwg2/Bh+fMS1cNyt4HAlclQiEgOx7nw1F5Mut2jBLY8W3BKRv1Dx1SL+QPIutgWVOl9DDe98LdtRxH3OpzjL+SkY8JndRuiMZ7mg11lWDVNEREREZNd+eg3euRZ8xZDRCs54GroMSPSoRCRGvNHO19gUNa1ecEudryLyVyq+WsQXjO0KjI1lZr42tPPVv/5H/NNO5SzndkKGjam5bTlp5Ed0zN3DymGKiIiIiFTPXwaz/gELpoUf73kEDHsGcjokdFgiElveQGzPtc1iaWM7X83tzU5aERGTiq8W8SV556s5rnovuGUYbPnyUbI+Gk9Hw2CTkcv1oSuYes2NOO368RERERGRONj8azhmYNNiwAZH3wDH/AMcmo+KNHXxynwt9zdycWp1vopIDTRbsYhZ1EzGxbYAnPZw52u9FtzylrD2f2ex26ovAPjEls4N5RNxt2inwquIiIiIxMcPL8O7Y8FfCpltYOgU2PvYRI9KROIk9pmvih0QkdhSBc0ivmBsDwiNZXa+BkJ1u5rnX7eI7f93GruVFRDE4KmcNuw24C22vrSazjqYiIiIiEis+Uph5k2w6IXw485Hhwuv2fmJHZeIxJUv1pmvkQWyzAWzGsosvmrBLRH5q+SsFKYgf+SA4IpkqyYbVzTztZbOV8Ng++cPEXq6P23LClhLiMe7D+LSa34h19MOiN3tHiIiIiIiAGz6BaYcFy682uzQ/xY4/00VXkWaodh3vtojr9PYzNfwONX5KiJ/pc5Xi3iDZvE1OQuTzmjm6y6Kr+VFbHj5HPIjMQMf2g3KT3mUa/qMDH87GiCug4mIiIiIxIBhwMIXYOaNECiDrPzwolqdj0r0yEQkQXyRomismoDMYmljO1/LfTpfFpHqqfhqEX+Mr8Y1VkXma/WxA8E/F1LwwunklxUQwOCx7DxOuehD9mm1b/Q55QFdyRMRERGRGPGWwHtj4cdXwo/3Pg7OeBqy2iR2XCKSULHufE2vlPlqGAY2W8PuZlXmq4jURMVXi5gdpcna+Vpj5qthUPz5Q6TNuZNWGKwmxMtdT+Tq4S+Q7kqv8tSKK3nJ+R5FREREJEVt+BmmXwhbl4PNAcf9E464Duyad4o0dxWZr7H5e5AWKZaGjPB5vdtZ/+KrPxgiEArXBFR8FZG/UvHVIr5guDDpTvLia5XYgbICNr98Lm1WfwnAu7YQOwbfz80HXV7tPsoDuo1CRERERCxkGLBgKrz/Dwh6IbsDDH8O9uyX6JGJSJLwxrj4WrlYWuYPNqjD1ux6BfC4k7MmICKJo+KrRfyBcFEzaWMHogtuhQ9cobXfUfTiMNqUFeDD4MGsXE694H16tN2vxn0o81VERERELFNeBO9cA4tnhB93GQinPwmZrRI7LhFJKhWdr7E5D3U5bDjsNoIhg3J/kBbprnrvwzxXttmStyFLRBJHxVeL+KILbjUsHybWXJWKr6Xz/oP743+Ti8HvhHi+S39uOvNlMt2Zu9yHuXqjiq8iIiIi0ijrFsFrI2Hb72B3wvHjod8YxQyIyE68kTswY9XoZLPZSHc5KPEGokXU+ir3VayP0tDMWBFpulR8tYgvGgKenIVJp91OC0q4auODZK79DoAZtiAlJ01kwiFj6nSAKPMr81VEREREGsEw4Jsp8OE/IeiDFrvD8Kmw+8GJHpmIJClfHBa39rjslHirxgfUhxbbEpFdUfHVIv4k73xtvX0R76Xdwm7+LXgxmJiZzel/e5fe7fvUeR+KHRARERGRBisrgLfHwC/vhB93HQynPQ4ZeQkdlogkt1hnvkLFOW6Zr3HFV50ri0h1VHy1iFl8Tbp8l1CIss/+w8FzJ+K0Gaw0WvLk3l259ezp5KTl1GtX0diBJO3uFREREZEktXYBvHYRFKwBuwtOvAsOvSIckCgisgvx6Hw1O1bNc976Mou26W6dK4vIzlR8tUg8Dgj1VrqVwlfOo8WarwB4J3gYD6RfwCfnn9egHBqveSuFVm8UERERkbowDPjqCZg9HkJ+yN0TzpwKHfsmemQikiK8MV5wCyo6Vhuc+RpQRJ+I1EzFV4v4ggYAriTpfDVWfUHpy+fSoryQcgzucO3F/8r/zr552Q0OANetFCIiIiJSZzu2wVujYdnM8OPup8Kpj0F6bkKHJSKpJZ6drw3NfC33KfNVRGqm4qtFKjJfE1x8DYXwfnoPzk/vIwuDpQSZtOfBnNZvKv+bthh/pEjcENHMV8UOiIiIiMiu/PENTB8JRWvB4YaBd8PBlypmQETqJRQy8AXjkPnqblznqxqVUkcoFKKgoKDOz8/NzcVuT44mO0ldKr5aJCliB0o2U/LyuWSt/RaAFwiw5dhbeOTocSz6oxCoKBI3hJl/k6ZbKURERESkOqEQfPkozLkTjCDk7QVnToP2ByR6ZCKSgnyVzl9jea7tiey7oZ2v5nbqfE1+BQUFPPjuQjyZ2bU+t7y0mLFD+pCXp4UhpXFUfLVIxYJbCbqav3IeO14eQZa3iB0Y/NPjYdi57/K3PY+KjCt8MAk0pvM1oAOKiIiIiNSgdCu8cTksnx1+3HMYDHkYPPVb5FVExGTmvUJsO1/NhbLMhbPqy2xU0oJbqcGTmU1mTm6ihyHNiIqvFjE7X+MeOxAK4v/kbhyf3U8GsJggD+/em3+fM4O2mW2jT3NGisKBUMM7X80DkW6lEBGpWX1vZYLw7UwiIilt9Zfw2iVQvA6cHjj5XjjwQsUMiEij+CoVX90xPNc2G4wqF3vrQxF9IrIrKr5axLwdIq6xA8Ub2PHKCDLWfgfAc/hYf9T1TD72Dhz2qn/0nZGMksZkvpoHIhVfRURqVp9bmaDidiYRkZQUCsHnD8And4MRglZdwjED+T0TPTIRaQK8kbsv3U57gxeOrgvzHLehna/mdup8FZHqqPhqkbgvuLXiY8pfvYAMbzElGNyc5mbo2TO4eK/jq326K9L52rjMV7PzVZmvIiK7oluZRKRZKNkEMy6D3z8JP97/HBj8AKRlJXZcItJkmJ2vaTE+z44WX7XglojEgIqvFokuuBXr4mswQODjf2H/4iE8wI8E+U+H/bj33DfokN2hxs2cVmS+KkRcRERERAB+/xRmjIKSjeBMDxdd+4xI9KhEpIkx7zCN9aLP6RYVX3WuLCLVUfHVIubt/DGNHSj8k/JX/oZn3fcATMbHusP/ztQBd+O07/qjjHa+NibzVVfzRERERJq3UBA+vQ8+vRcwoE33cMxA226JHpmINEFef3yanMy7O8sbWHyNNiq5dZeoiOxMxVeL+GIdO/DbbLzTL8LjK6EIg7FuB0PPfJ0rugyq0+auSOarYUAwZOCw1y8vxzCM6AqOsb7qKCIiIiJJqHgDvH4prPos/LjP3+Dk/4A7I7HjEpEmq6LzNbYNQGZWa2OLr2pUEpHqqPhqkWjsgNWdr0E/wY/uwDH/MdKA7wkysd2+PHDem+zRYo8678bpqCi2+oOhnRbkqk3lVR91QBERERFpZlZ8HM53Ld0MrkwY8hAccHaiRyUiTVz8Ol+tWXBL58oiUh0VXy1SseCWhSswFvyB95W/kbZ+EQCP42P1IZfy4sAHcDvc9dpV5Y5cfzBU74OCedAD5diIiIiINBvBAMydCJ89ABjQrmc4ZqB1l0SPTESaAV8wXNSM9d2X5vlxub9hMX3KfBWRXVHx1SJm8dWyK3JLZ+KfcSlpvlIKMPi7y8YZQ19kTPehDdqds1LMQEMW3TIPJg67LXbRChI3wWAQv9+fsNf3+/04nU7Ky8sJBht2dVkSJ1k+P4fDgdPpxGaz8KKXiIhUKPwzHDOw5svw474j4aSJ4EpP7LikSTAMg0AgkLC5RLLMZ2TXAj4vHbMd5Gc6KC8vr/I9Kz/DTEeIjtkOMhyhnV5nV8z5qFm0VfFVRKqj4qtFLIsdCPgIzb4d+9dP4gK+IchdbTrz8Llvsnfe3g3ercNuw2YLZ742ZNGtaIZNLBcUk7goKSlh7dq1GEb9i/BWMQyD/Px8/vjjDxXOUlAyfX4ZGRm0b98et7t+dwOIiEgtfv0Q3rgcyraBOxtOfQR6Dkv0qKSJ8Pl8rF+/nh07diRsDMk0n5GatTICTDi2LR6nnZUrV1b5npWfYV4oyIRj2+Jy2HZ6ndpkZGTgtoXPsRU7ICLVUfHVIv5IN2mjukK3r8L3yvm4N/wIwEN4WXHgBUwf9Cgep6dR47PZbLjsdnzBUIM6X8sDyrBpCoLBIGvXriUjI4M2bdokbKIZCoUoKSkhKysLu10F/VSTDJ+fYRj4fD42b97MypUr6dKli36WRESsEPTDnDvhy0fDj9sfAMOnQquGNwGIVBYKhVi5ciUOh4MOHTrgdrsTMidNhvmM1K5ghw9nUTmZaU52a1l1cT8rP8MdvgD2bTtwO+x0bpNVp20qz0fP6+Hh+z+KSHfrZ0lEdqbiq0XMBakaXHxd8jaBN67A7S9lGwZXOEOcftpzXNfrPMvG6HTY8AUbFjtg3kah4mtq8/v9GIZBmzZtSE9P3C2DoVAIn8+Hx+PRZDcFJcvnl56ejsvlYvXq1dHxiIhIIxT8Aa9dDGu/CT8+5HI48S5wpiV2XNKk+Hw+QqEQu+++OxkZGbVvECPJMp+RXXMFbNicIVxu105zPSs/Q8MewOYMgMNerzlldD66uYjWGQ6dL4tItVR8tUg087W+t+UHvBgf/BPbt1NwAvMJcHur3Xns3Dfp1rqbpWM0c199wfrHDlSs3qiJSVOgW6ukqdDJkoiIRZbOhDevhPICSGsBpz0OPU5N9KikCdMxXOoiFOkbshHb8xfz/CjUgGg282fZYVfmazyFQiEKCgrq/Pzc3Fz93ZGEUfHVIg1acGvrCgKvXoBz488A3IuXZQecyZuDJ5PpzrR8jGZXbqAhma+KHRCRZqa+EzoIT+pERFJKwAcfjYevngg/7nAgnDkVWnZK6LBERAAMwsXQWPeO2KPF14Ztb26W7tb5crwUFBTw4LsL8WRm1/rc8tJixg7pQ15eXhxGJrIzFV8tYi645XLW8ajw8+sE3hqD07+DLYS41BHk1CFPcFPvkTHrSowWXxsQO+D1q/gqIs1LfSZ0UDGpExFJGdtXwfSRsO778OPDRsOACeDUIoYikhzMRlR7zIuv5usZGIZRr3Py8Dbh//Y4db4cT57MbDJzchM9DJFaqfhqgVDIIBC5RFZr56u/DGPWOGwLpuIEPiPALbn5TDr3DfZvt39Mx+l0hA8g/gbEDlRkvqpNv6lpSHdfY+Xk5MT19Rpr1apVdO7cmYULF9K7d+9EDweApUuXctFFF7Fo0SK6devGokWL4vbad9xxBzNmzOCHH36I22smiiZ0ItJkLXkb3hoD3kLw5MLpT0K3QYkelTRTmo/WrrnOR80YgL8WQydMmMCbb77J3LlzLXkde6X9hwxw1KPYW7lbVp2vIlIdFV8t4K90G79rV5mvW34j+Mr5ODb/QgiDifj4eb9TeO/UZ8lJi/3BvyJ2oP6dr2WRzldl2DQ99e3ua6zy0mKuHXQATmfd//xcdNFFPP/880ycOJF//OMf0a+/+eabnHHGGRgNyGZKdePHjyczM5Nly5aRlVW3FVmtcv3113PhhRfG9TVFRMQi/nKYfRt883T48W6HwPDnIHf3xI5LmjXNR1NTPOaj5v/Wvzai3nDDDYwePdqy16m8//BnWffqa+Wc2LT6rgEjIs2Ciq8WMCMHYBedrz+8QvCdq3EEytlEiJH2AINPfpCXDroybosfmQtu+QMN6XwNF1/TVHxtklKhu8/j8XDvvfdy+eWX07Jly0QPxxI+nw+3u2G3dq5YsYLBgwez5557xuX1KsvKyiLUgOxoERFJsK0rYPpFsOHH8OMjroHjbgOHK6HDEgHNRxMl2eejZlHb/pdz5qysLDIyMigqKqrzvnbFZrNht9kIGUa9F90yx5jmdGhhYxGpli7LWMBfKUPV9dfiq28Hxpuj4Y3LcATK+YQAQ1rkcceln3HVwVfF9Y+zMzI2fwM6X6OxA8qwkQQZMGAA+fn5TJw4scbnTJgwYafbsB5++GE6deoUfXzRRRdx+umnc/fdd9OuXTtyc3O58847CQQC3HjjjeTl5bHbbrsxderUnfa/dOlSDj/8cDweDz179uTTTz+t8v2ff/6Zk08+maysLNq1a8f555/Pli1bot/v378/Y8aM4dprr6V169YMHDiw2vcRCoW488472W233UhLS6N3797MmjUr+n2bzcaCBQu48847sdlsTJgwodr91PR6uxrn008/TYcOHXYqrp522mlcfPHFQDh24Kijjqry/WeeeYbu3bvj8Xjo1q0bTzzxRPR7w4cPZ8yYMdHH1157LTabjaVLlwLhSXhmZiYfffQRAK+99hq9evUiPT2dVq1aMWDAAEpLS6t9jyIiUkc/vw5PHRMuvKbnwXnT4YQ7VXgVqQfNR+M/HzVPXW1UnY9OmDCBAw88sMprNXY+ekiXDnz12VxCRv3mo9G8V0X0iUgN9NfBAmaGqsNuw1E5CXzTUoJP98e26AVCGEzAy6Ndj+eDKxZxUIeD4j5OdyS4JtCgzFdzwS39yEhiOBwO7r77bh577DHWrl3bqH19/PHHrFu3jnnz5vHggw8yfvx4hgwZQsuWLfn666+54ooruPzyy3d6nRtvvJHrr7+ehQsX0q9fP0455RS2bt0KhG+XO+644+jTpw/fffcds2bNYuPGjZx11llV9vH888/jdrv54osvmDx5crXje+SRR3jggQe4//77+fHHHxk4cCCnnnoqv/32GwDr169nv/324/rrr2f9+vXccMMNNb7Xv75ebeM888wz2bp1K5988kl0H9u2bWPWrFmMGDGi2td48cUXuf322/n3v//NL7/8wt13381tt93G888/D8AxxxxTJY/r008/pXXr1tGvffvtt/j9fg4//HDWr1/Pueeey8UXX8wvv/zC3LlzGTp0aLO8lU9ExBL+MnjnWnjtYvAVwx6HwxWfw74nJnpkIilH89H4z0fNGWDB9u2xn48G/Bxw0CGsW7euXvNRs1M2rbb1X0Sk2dJfBwuYsQPRyAHDgIUvEHr6aBxblrGeEANt5WSf+G9mnPMWLdMTc4tKtPM12IDO14AyXyXxzjjjDHr37s348eMbtZ+8vDweffRRunbtysUXX0zXrl3ZsWMHt9xyC126dGHcuHG43W4+//zzKtuNGTOGYcOG0b17d5588klatGjBs88+C8Djjz9Onz59uPvuu+nWrRt9+vThueee45NPPuHXX3+N7qNLly7cd999dO3ala5du1Y7vvvvv5+bb76Zc845h65du3LvvffSu3dvHn74YQDy8/NxOp1kZWWRn5+/y4ytv75ebeNs2bIlJ598Mi+99FJ0H6+99hqtW7fm2GOPrfY1xo8fzwMPPMDQoUPp3LkzQ4cO5brrruOpp54Cwh0PS5YsYfPmzWzfvp0lS5ZwzTXXRCe7c+fO5eCDDyYjI4P169cTCAQYOnQonTp1olevXlx11VWNyhELhUJs27atzv8UqSAiTcaW3+CZAbBgKmCDo2+EC9+BFh0TPTKRlKX56MNA/OajZsHz3bdmxHw+2qv3gaSn138+as4c3VpsS0RqoMxXC/ginaQuhw28JfDe9fDjy9iBDwlwU1YLJp01iyP2OCKh4zQzXwMNKCyU+8zOVx1QJLHuvfdejjvuuF1eXa/Nfvvth91ece2pXbt29OzZM/rY4XDQqlUrNm3aVGW7fv36Rf/b6XRy0EEH8csvvwDwww8/8Mknn1Q7KVuxYgX77rsvAH379t3l2IqKili3bh1HHFH178URRxzBDz/8UMd3WOGvr1eXcY4YMYJRo0bxxBNPkJaWxosvvsg555xT5f+ZqbS0lBUrVnDJJZcwatSo6NcDgQAtWrQAoGfPnuTl5fHpp5/idrvp06cPQ4YMYdKkSUC486B///4AHHDAARx//PH06tWLgQMHcuKJJzJ8+PBG5arVZxGP8tJixg7pQ15eXoNfT0QkKfzwCrx7HfhLIbMNDH0a9j4u0aMSaRI0H62fxsxHb7rzP4Cd1199Jebz0UMPD8dq7ddr//rNRyMFYo8W2xKRGqj4agEzdqCHYw2hp2/BvnU5QQxux8v3e/dn9tAXaJPZJsGjrMij9TcodiCS+arYAUmwo48+moEDBzJu3DguuuiiKt+z2+073Q7k9/t32ofLVTXfzmazVfu1+nRAlpSUcMopp3Dvvffu9L327dtH/zszM7PO+7TCX1+vLuM85ZRTMAyD9957j4MPPpjPPvuMhx56qNr9l5SUADBlyhQOPfTQKt9zOMIXa2w2G0cffTRz584lLS2N/v37s//+++P1evn555/58ssvoycvDoeD2bNn8+WXX/Lhhx/y2GOP8c9//pOvv/6azp07N/j/Qyos4iEiYgnfDnj/Rlj4Qvhxp6Ng2DOQnZ/YcYk0IZqP1k9j5qMff/g+e+93APO//JzHHn242v1bNR8999LR4efa6zcfNXNp07Q+iojUQMVXC/j8Qc51zGF88L/Yt/r5kxAjbOUMOHY87x11C3ZbchQsnZHM18bEDqjzVZLBPffcQ+/evXe6TapNmzZs2LABwzCii9ktWrTIstf96quvOProo4HwlfQFCxZEg/sPPPBAXn/9dTp16oTT2fA/rTk5OXTo0IEvvviCY445Jvr1L774gkMOOaRxb6CO4/R4PAwdOpQXX3yR5cuX07Vr150WNDC1a9eODh068Pvvv9eYwQXhnK0pU6aQlpbGv//9b+x2O0cffTT/+c9/8Hq9VTorbDYbRxxxBEcccQS33347e+65J2+88QZjx45t3JsXEWnqNv0C0y+CzUsBG/T/RzhqwK75m4jVNB9tuPrMR996/VW6L19Ol333jfl89OBDDiME0c+urvPRaOarOl8bxIwI++vFh5rk5uZW2wEtksxUfG2s8iJ2+/jvTHS9A8BM/NyYmc1jw9/iuM7JdWuX2fkaaEjx1a/ia1NWXlqcUq/Vq1cvRowYwaOPPlrl6/3792fz5s3cd999DB8+nFmzZvH++++Tk5PT6NcEmDRpEl26dKF79+489NBDbN++Pbri6ujRo5kyZQrnnnsuN910E3l5eSxfvpyXX36ZZ555JnrVvS5uvPFGxo8fz957703v3r2ZOnUqixYt4sUXX2z0e6jrOEeMGMGQIUNYvHgxf/vb33a5zzvuuIOrr76aFi1acNJJJ+H1evnuu+/Yvn17dILav39/rrvuOtxuN0ceeWT0azfccAMHH3xwtCPi66+/Zs6cOZx44om0bduWr7/+ms2bN9O9e/dGv3cRkSbLMGDRi/DeDRAog6x24W7XzkcnemQidab5aN00t/no4CFDWLb0F/62i6IqWDMfzcrKoqjczzfffM13X35W5/moOl8bp7S0lEfe/4GM7Nxan6uIMElVKr42xvofCL16IXnbVxIw7NwTHMicvdfz0fCXaZ/dvvbt48zlaHjma1k0dkAHlKYmNzeXsUP6xPU1c3JyorcHNdSdd97JK6+8UuVr3bt354knnuDuu+/mrrvuYtiwYdxwww08/fTTjXot0z333MM999zDokWL2GeffXj77bdp3bo1QLQ74Oabb+bEE0/E6/Wy5557ctJJJ9X7yuzVV19NYWEh119/PZs2baJHjx68/fbbdOnSpdHvoa7jPO6448jLy2PZsmWcd955u9znpZdeSkZGBv/5z3+48cYbyczMpFevXlx77bXR5/Tq1Yvc3Fz23XffaL5X//79CQaD0bxXCP9szJs3j4cffpiioiL23HNPHnjgAU4++WQMwyAYDFZ57UAgQCgUoqCgALfbXeV7uiouIs1CpfUGANjrWBg6BbISH3klUleaj9Zdc5uPtshtyaoVv3HmOefscp9WzEcjjcpkZdU8H61WpPja3CP6zDl5XeXm5kb/Oz1LEWHStKn42hCGAd8+g/HBOOxBP38YTq7x3crKrA58e+EwnPbk/N/qtJuZr43pfG3eB5SmyG63x/3KYX1Xk582bdpOX+vUqRNer3enr19xxRVcccUVVb52yy237HJf5iqnla1atarKa5nZXeeee26N4+zSpQszZsyo8fvVvU517HY748eP3+UqunW5fa2m16ttnOYY1q1bV+33xo8fz3XXXVfla+edd94ui7R2u51t27ZV+Vrv3r13ykTr3r07s2bNqnYfwWCQjQU7sFXq2gj4fBSX+/nwmzWUVopT01VxEWkWNvwcjhnY+hvY7HDsP+HIsaALT5JiNB/VfLSmMXy26Fe8gSB7t6m6ONeECRO4/fbbKSoqin6tsfPRP7btAGCfrl1rnI9WJxo70MzPlRuyyG12du3PFWkKkrNKmMzKC+Htv8OSt7ABb+PnBmdvfN59OSA3N2kLr1A587X+na9es/iqWylEJIFsDkeVW+ZCDgc2m530zGwI6e+TiDQThgELpsGsf0CgHLI7wPBnYc/DEz0yERFLmYVRsys1luw28zXrt50ZO+BR5qsWuRWpQfJWCpPRnwswpo/EVrAaHwY34+Xr3Q7k1l6Pc/sba3A74nBEaASX3cx8rX/xtTwSO5DuVnFDREREJGHKi+Dda+Hn18OP9zkBzngKMlsldFgiIrFgFjZtxP5c2x6p8IbqWX01C8TuJtKo1JD4AEV9ieyaiq91YRjw9WSMD2/FFgqwkhBns4Oj+l3LpwPuYeZPm4A1uJP8SpfLaXa+1j92oEyxAyJikeqyW3fF4XBEVwsWEWnW1v8QjhnY9jvYHDBgPPT7u2IGRKTJMiKBqvY4TAVt0eJr/bYzi69pSV4PqKuGxAco6ktk11R8rc2ObfDWGFj2HjbgdfyMTXPx8OmvcUb3MwDwBcJdoS5Hcv+xNTNfG7Lglpn5qhUcRaSxqsturYkRDNIuNwOnU4crEWnGIusN8MEtEPRBi91h+HOw+yGJHpmISExFO1/jGTtQz+prNHYgyRanbkwHq+IDRKyls9ld+eNbjNcuwla4Fi8G11PO/PY9+eSs19ir5V7Rp/kit/G7k7z46orEIgQateBWch1QpGH+usiRSLz9Nbu1JrX2x0Z/ltUZKyJNVFkBvHM1LHkr/LjrIDhtEmSoy0hSm+ajUhvDMCplvsYzdqB+24WMEGCQlmTnyupgFUkeKr5WJxSC+Y9hzLkTWyjAckKcxQ76HXwFXwx8AI/TU+XpfrPzNclvM3BGisO+hmS+BpT52hSYxS6fz0d6enqCRyNNQSAQqPNzYxEf4POWEzQMfCEVX0WkCfpzAUwfCQWrwe6CE+6Ew66MTwuYSIy4XC4AduzYofmo7FLlGmg8/uyZr1HfzNeA14s/aOD0JF95RR2sIskh+f46JFrpVnjzSvjtA2zAy/gZ63bw4Kkvck7Pc6rdxMxQTfrOV3vDOl+DISMaraAVHFOb0+kkIyODzZs343K5EhaMHgqF8Pl8lJeXK5w9BZmfX2lpKdtKvNjq8BkaoRCtsj04nU4CgQABn49QHTpfQ8Eg5eXGztsZBj5vOVu3bGbdDjtBdb6KSFNiGPDVkzD7dgj5IXdPOHMqdOyb6JGJNJrD4SA3N5dNmzYBkJGRkZBsd81Hk18wFMII+ADwlXsJ/CX41erPMOD3YQR8+H1BysvrEI9lGOzYsYMtWzYz5/cSjj6gfaPHICJNk4qvla2ej/HaxdiK11GOwTWUM79tVz456zW6tu5a42apEzvQsMxXb6Dixl/FDqQ2m81G+/btWblyJatXr07YOAzDoKysjPT0dC2klILMzy8tLY0SbwCbrQ7FVyNEiSdc8A+FQhSX++u8XXEN2wUNg3U77PxR7m70exIRSRo7tsFbo2HZzPDj7qfCqY9Bem5ChyVipfz8fIBoATYRNB9NfsGQwabCcgBcO9J36n61+jMs8wXZWuojzWknUJhW5+2+WlvGjF9KGXhQbM6VG5PdKiLJQcVXCMcMfPEQxsf/xmYEWUaQsyijb58L+WrQ42S4Mna5eXTBLWdyH7TN2AF/PTtfy/0VxVoVX1Of2+2mS5cu+Hy+hI3B7/czb948jj766OitZ5I6zM/vgAMOYPb360ivQ45UWWkx5x6ST25uLgUFBXz4zZpGbmfDF7Kp41VEmpY/voHXLobCP8DhhoF3w8GXKmZAmhyzIaBt27b4/f6EjEHz0eS3qaicy9/8Cpfdzqzrjt7p+1Z/hl+v3MqEd3+iS7ssJv+tW522cblcXPfBFxjELqJP2a0iqU/F15LN8MZlsOJjbMD/4WOs08Z9g59hZJ+RddqFP9L56kr6zlczdqB+na/mYltuhx2HXZP/psBut+PxeGp/Yow4HA4CgQAej0eT3SRQ36vpmZmZBAIBXC4XpX4gVPtEs9QfLvx7PB7cbnfMtxMRSSmR9QaYcyeEAtCyM5w5DTr0TvTIRGLKUccFOGP12pqPJrdgSZA/i4NkpdmqPXex+jNMS/PwZ3EQjydQr3Mlr7k+SgwblZTdKpLakqJaOGnSJDp16oTH4+HQQw/lm2++2eXzp0+fTrdu3fB4PPTq1YuZM2c27IVXfgaTj4QVH4MznU8POIt/t9qDj0d9XefCK1R0vrqTPA/VGSmc1rfztSxSfE1zJff7E2nuQqEQ27Ztq/O/UCSCxLya/sQny2v99+C7C+tVqBWR5FLfOVdzkrD56I7t8L+zI/muAdhvKFw+T4VXEWn2zPPstDidZ5vF08p3ftZFmS98vqy7REXqpjnORxPe+frKK68wduxYJk+ezKGHHsrDDz/MwIEDWbZsGW3btt3p+V9++SXnnnsuEydOZMiQIbz00kucfvrpfP/99/Ts2bPOr2v7+klY+jQYIWjdFc56nqPbdGNhoJx0V/1W3fSnSOZrRexAwzpfdTARSW6NuSVJV9NFmr76zrmak0TNRwEc/xsOji3gSIOT74W+FylmQESEirVH4tXk5IkWX4O1PLOqsjqeLyu7VaT5zkcTXnx98MEHGTVqFCNHhjtNJ0+ezHvvvcdzzz3HP/7xj52e/8gjj3DSSSdx4403AnDXXXcxe/ZsHn/8cSZPnlzn13V8/QTk2KH332DQfeDOZMGqbWwp8QIF9XoPv28pBZI/dsAsDq8vLGfWz+vrvJ35/jzqfJVmqL6TJKiYKDV0gtWYiZmKqCJSk/rOuZqTRM1HAWylm6Bz13DMQH5P/iwo46e1BY19SxJjgUCQH7bacCzeiNOpBoVUpM8w+a3YHD4P3VXnq3nnV31iB2oqapqdryXeQI3ny6FQiNLiwipfKy7cTjBoUF5ayLZtO6+rYb6esltFmu98NKHFV5/Px4IFCxg3blz0a3a7nQEDBjB//vxqt5k/fz5jx46t8rWBAwfy5ptvVvt8r9eL1+uNPi4sDP+hXLfDyZbDbsbYcyAs/hWA8W8t4fs/CqvdjyMtM/rfQW9ptc/ZtBoWLiyp8rWWLVtG/3v79u3VbledWGz35+9b8G5ezXebYeSiH6t8ry7vLxhKZ+HChZaMs/K29d0uKyuLLVu2sGjRIpzOuv8IJ9Nn0dy38/v99f4ME/Gz1rJlS7Zv386THyzE7dn1wnsmX/kOrhzYp97bWrXdxrWr8GRk1bpd+Y4SVq92UVRUVO/t1qyxsWXLFtasWROX10uF7SpvC8R1O32GzWs7c9s/08J/HwoLC8nJyYl+Ly0tjbS0nVdobsicq7mIx3wUap6TLs7ox+ZDx8N6P6xfyMfLtnD/7N+q3Udd5mtWbld523hvV99tE7bdd3NSY5xJvl3lbeP+s6bPMOm389dwHur3+/njjz/45zPv4Mms2zH0r3PnygrK/Hg3r8YLjHxoZbVjDXpLCZUUYHPvnAn76GvzcLuq3rnw19cr3L61yrGgJuF5wuqkn5c0drusrCy2bdvG+oCTzOzaz9VS5f1V3haS/9ygodtpPloPRgL9+eefBmB8+eWXVb5+4403Gocccki127hcLuOll16q8rVJkyYZbdu2rfb548ePNwD90z/90z/90z/9078m/2/8+PGWzbmai3jMRw1Dc1L90z/90z/90z/9ax7/NB/dWcJjB2Jt3LhxVToTtm3bRufOnfn5559p0aJFAkcmDVVcXEyPHj1YsmQJ2dm137IhyUefYWrT55f69BmmvsLCQnr27MnKlSur3JJYXZeBJAfNSZsW/R1NffoMU58+w9SnzzC1aT5adwktvrZu3RqHw8HGjRurfH3jxo3k5+dXu01+fn69nl9Tu/Puu+9epS1aUkdRUREAHTt21GeYovQZpjZ9fqlPn2HqMz+3vLy8On2GDZlzNRfxmI+C5qRNjf6Opj59hqlPn2Hq02eY2jQfrbuErqDkdrvp27cvc+bMiX4tFAoxZ84c+vXrV+02/fr1q/J8gNmzZ9f4fBEREZHmriFzruZC81ERERGR2GvO89GExw6MHTuWCy+8kIMOOohDDjmEhx9+mNLS0ujKZxdccAEdO3Zk4sSJAFxzzTUcc8wxPPDAAwwePJiXX36Z7777jqeffjqRb0NEREQkqdU252rONB8VERERib3mOh9NePH17LPPZvPmzdx+++1s2LCB3r17M2vWLNq1awfAmjVrsNsrGnQPP/xwXnrpJW699VZuueUWunTpwptvvknPnj3r9HppaWmMHz9eGRQpTJ9h6tNnmNr0+aU+fYapryGfYW1zruYs3vNR0O9hqtPnl/r0GaY+fYapT59hatN8tO5shmEYiR6EiIiIiIiIiIiISFOT0MxXERERERERERERkaZKxVcRERERERERERGRGFDxVURERERERERERCQGVHwVERERERERERERiYEmWXydNGkSnTp1wuPxcOihh/LNN9/s8vnTp0+nW7dueDweevXqxcyZM+M0UqlJfT7DKVOmcNRRR9GyZUtatmzJgAEDav3MJfbq+3toevnll7HZbJx++umxHaDsUn0/v4KCAkaPHk379u1JS0tj33331d/SBKvvZ/jwww/TtWtX0tPT2X333bnuuusoLy+P02ilsnnz5nHKKafQoUMHbDYbb775Zq3bzJ07lwMPPJC0tDT22Wcfpk2bFvNxSu00J01tmo+mPs1HU5/mpKlN89HUpjmphYwm5uWXXzbcbrfx3HPPGYsXLzZGjRpl5ObmGhs3bqz2+V988YXhcDiM++67z1iyZIlx6623Gi6Xy/jpp5/iPHIx1fczPO+884xJkyYZCxcuNH755RfjoosuMlq0aGGsXbs2ziMXU30/Q9PKlSuNjh07GkcddZRx2mmnxWewspP6fn5er9c46KCDjEGDBhmff/65sXLlSmPu3LnGokWL4jxyMdX3M3zxxReNtLQ048UXXzRWrlxpfPDBB0b79u2N6667Ls4jF8MwjJkzZxr//Oc/jRkzZhiA8cYbb+zy+b///ruRkZFhjB071liyZInx2GOPGQ6Hw5g1a1Z8BizV0pw0tWk+mvo0H019mpOmNs1HU9//t3fvMVXXfxzHXwieI+hRI+JmgCJTwchKp0PbiGbpama5pkslWF4ydJkXBHOGSQozaytXWmlprXTmbQZmkWl5raXSrJBAMmsDl0vLS8rlfH5/NM/PI6By5HD6wvOxnT/4fj+f7/f9PR8PvnjzPQcyafNpdc3XgQMHmqlTp7q+rqurM5GRkSYvL6/B8aNHjzYPP/yw27ZBgwaZp59+2qt1onFNXcOr1dbWGofDYdasWeOtEnEdnqxhbW2tGTx4sFm5cqVJS0sj7PpQU9dv+fLlJjY21lRXV7dUibiOpq7h1KlTzf333++2bebMmWbIkCFerRPXdyNBd86cOaZv375u28aMGWOGDRvmxcpwPWRSayOPWh951PrIpNZGHm1dyKQ3p1V97EB1dbUOHjyooUOHura1a9dOQ4cO1f79+xucs3//frfxkjRs2LBGx8O7PFnDq124cEE1NTUKDg72Vpm4Bk/XcOHChQoNDdWECRNaokw0wpP127p1q5KSkjR16lSFhYXpjjvu0OLFi1VXV9dSZeMKnqzh4MGDdfDgQddbwSoqKrRt2zY99NBDLVIzbg5Z5r+HTGpt5FHrI49aH5nU2sijbRNZpnEBvi6gOZ06dUp1dXUKCwtz2x4WFqajR482OKeqqqrB8VVVVV6rE43zZA2vlpWVpcjIyHoverQMT9Zwz549WrVqlYqLi1ugQlyLJ+tXUVGhL7/8UuPGjdO2bdtUXl6ujIwM1dTUKCcnpyXKxhU8WcOxY8fq1KlTuvfee2WMUW1traZMmaLnn3++JUrGTWosy/z999/6559/FBgY6KPK2i4yqbWRR62PPGp9ZFJrI4+2TWTSxrWqO1+B/Px8rVu3Tps3b1aHDh18XQ5uwNmzZ5Wamqp33nlHISEhvi4HHnA6nQoNDdXbb7+t/v37a8yYMZo3b55WrFjh69Jwg3bt2qXFixfrzTff1KFDh7Rp0yYVFhYqNzfX16UBgOWQR62HPNo6kEmtjTyK1qxV3fkaEhIif39/nTx50m37yZMnFR4e3uCc8PDwJo2Hd3myhpctXbpU+fn5+uKLL3TnnXd6s0xcQ1PX8NixYzp+/LhGjBjh2uZ0OiVJAQEBKi0tVc+ePb1bNFw8eQ1GRESoffv28vf3d22Lj49XVVWVqqurZbPZvFoz3HmyhvPnz1dqaqomTpwoSUpMTNT58+c1efJkzZs3T+3a8bva/7LGskznzp3b9B0GvkQmtTbyqPWRR62PTGpt5NG2iUzauFb1r9dms6l///7asWOHa5vT6dSOHTuUlJTU4JykpCS38ZJUVFTU6Hh4lydrKElLlixRbm6utm/frgEDBrREqWhEU9ewT58+OnLkiIqLi12PRx55RCkpKSouLlZUVFRLlt/mefIaHDJkiMrLy10/pEjSzz//rIiICEKuD3iyhhcuXKgXaC//4GKM8V6xaBZkmf8eMqm1kUetjzxqfWRSayOPtk1kmWvw7d/7an7r1q0zdrvdrF692vz0009m8uTJpmvXrqaqqsoYY0xqaqrJzs52jd+7d68JCAgwS5cuNSUlJSYnJ8e0b9/eHDlyxFeX0OY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      "text/plain": [
       "<Figure size 1600x1200 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# code from https://github.com/papousek/duolingo-halflife-regression/blob/master/evaluation.py\n",
    "def load_brier(predictions, real, bins=20):\n",
    "    counts = np.zeros(bins)\n",
    "    correct = np.zeros(bins)\n",
    "    prediction = np.zeros(bins)\n",
    "    for p, r in zip(predictions, real):\n",
    "        bin = min(int(p * bins), bins - 1)\n",
    "        counts[bin] += 1\n",
    "        correct[bin] += r\n",
    "        prediction[bin] += p\n",
    "    np.seterr(invalid='ignore')\n",
    "    prediction_means = prediction / counts\n",
    "    prediction_means[np.isnan(prediction_means)] = ((np.arange(bins) + 0.5) / bins)[np.isnan(prediction_means)]\n",
    "    correct_means = correct / counts\n",
    "    correct_means[np.isnan(correct_means)] = 0\n",
    "    size = len(predictions)\n",
    "    answer_mean = sum(correct) / size\n",
    "    return {\n",
    "        \"reliability\": sum(counts * (correct_means - prediction_means) ** 2) / size,\n",
    "        \"resolution\": sum(counts * (correct_means - answer_mean) ** 2) / size,\n",
    "        \"uncertainty\": answer_mean * (1 - answer_mean),\n",
    "        \"detail\": {\n",
    "            \"bin_count\": bins,\n",
    "            \"bin_counts\": list(counts),\n",
    "            \"bin_prediction_means\": list(prediction_means),\n",
    "            \"bin_correct_means\": list(correct_means),\n",
    "        }\n",
    "    }\n",
    "\n",
    "\n",
    "def plot_brier(predictions, real, bins=20):\n",
    "    brier = load_brier(predictions, real, bins=bins)\n",
    "    bin_prediction_means = brier['detail']['bin_prediction_means']\n",
    "    bin_correct_means = brier['detail']['bin_correct_means']\n",
    "    bin_counts = brier['detail']['bin_counts']\n",
    "    r2 = r2_score(bin_correct_means, bin_prediction_means, sample_weight=bin_counts)\n",
    "    rmse = mean_squared_error(bin_correct_means, bin_prediction_means, sample_weight=bin_counts, squared=False)\n",
    "    print(f\"R-squared: {r2:.4f}\")\n",
    "    print(f\"RMSE: {rmse:.4f}\")\n",
    "    ax = plt.gca()\n",
    "    ax.set_xlim([0, 1])\n",
    "    ax.set_ylim([0, 1])\n",
    "    plt.grid(True)\n",
    "    fit_wls = sm.WLS(bin_correct_means, sm.add_constant(bin_prediction_means), weights=bin_counts).fit()\n",
    "    print(fit_wls.params)\n",
    "    y_regression = [fit_wls.params[0] + fit_wls.params[1]*x for x in bin_prediction_means]\n",
    "    plt.plot(bin_prediction_means, y_regression, label='Weighted Least Squares Regression', color=\"green\")\n",
    "    plt.plot(bin_prediction_means, bin_correct_means, label='Actual Calibration', color=\"#1f77b4\")\n",
    "    plt.plot((0, 1), (0, 1), label='Perfect Calibration', color=\"#ff7f0e\")\n",
    "    bin_count = brier['detail']['bin_count']\n",
    "    counts = np.array(bin_counts)\n",
    "    bins = (np.arange(bin_count) + 0.5) / bin_count\n",
    "    plt.legend(loc='upper center')\n",
    "    plt.xlabel('Predicted R')\n",
    "    plt.ylabel('Actual R')\n",
    "    plt.twinx()\n",
    "    plt.ylabel('Number of reviews')\n",
    "    plt.bar(bins, counts, width=(0.8 / bin_count), ec='k', lw=.2, alpha=0.5, label='Number of reviews')\n",
    "    plt.legend(loc='lower center')\n",
    "\n",
    "\n",
    "plot_brier(dataset['p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "plt.figure(figsize=(16, 12))\n",
    "for last_rating in (\"1\",\"2\",\"3\",\"4\"):\n",
    "    plt.subplot(2, 2, int(last_rating))\n",
    "    print(f\"\\nLast rating: {last_rating}\")\n",
    "    plot_brier(dataset[dataset['r_history'].str.endswith(last_rating)]['p'], dataset[dataset['r_history'].str.endswith(last_rating)]['y'], bins=40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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Qka1jit1yumjXk62yRtHr0OizyFFZ8U/591nGy+y9mERqtqEn0cXWgl7NAnivaUWcbCzucTUhnh6JaVn0XHKAI1GJWFuomPN2A16s+XCWYdl74SZj1hw36S0Ew93Z4EpudG7gS5taXg/0gS4rR0f45UR2n7vB+mPXOB9nuNYzFV34skNt84aipMXD4WXk7PsBTcoVAHQopPu3wu65D6FyK7i97WeOVke3hfvYFxlPDS8Hfh/Q7J7jJM/FphAybReWahWHxobgYP30/N8k798PRoLEYpBfsqdHfHw8kzdEsC4iidRMLe/b7eYz7VwA1taYwk3byrx4fhIVkgxbX8XZVuV3z0Go/Z9l6YFoLt1MA8DBSsN7Tf15u7E/GpVCRraWjGwdGdlaMnN0t59ryci5k5Z5+6uviw0NKrjg62IjM6nFE+FaYjrv/bifc7G3cLKx4McejWjo/3C3sczI1jJz61kW/xOJt5MNnRuUp2MDX8o725T4tbK1Ohb/E8mMLWdJy9KiUSn0fi6AISFVsbUsIhC9ehgOLITjv4A2E4BEvR1/aUJ4odtoylcKLPC02OQM2s36HzduZfFmIz8mv16nyPrN2X6O/9sYQYvq7izp+ex9t/NxJO/fD0aCxGKQX7KnR8SlaF7/8QgpmTpa2EayUD8BjT6bPX592VehjyGTXk9g7DqaX5yJTU4SehQy676HJvQL1v97iznbz/FvzK0Hrou7gxX1/Zxp4O9CfT9n6vg6Y2P56GZWClESzsWm8O6i/VxPysDL0ZplvZ+lmuejm/CV+xb3KD5wXU1M5/O1J41LzZR3tmH8K4GG2cR6PSRdhphTEHsSzvx1Z59l4AwBLMp+iRPOISzq0xyfewSze87doNuifej1MPWNunQu4rb9a7N3c/RKEpM61eatZyuUTGMfE/L+/WAkSCwG+SV7OsSnZvH63N1cuJlOVetkftN8gn1OPGfdWrKu+jegmA72tslOoHnkDALj/jIkOJaHdv+Hrlo7Np+OYe72cxy9koRapWCtUWFtocYq96uFGmsLFdYaNVa3v1pbqNCoVZyNSeHktWRydKZ/mmqVQk1vBxpUcKFBBRfqV3Cmgqut9DaKMutwVAK9lhwgMS2bSu52/NS78UPpyStrdh49y8/rN+Kaeo4aShRN7KKppI9ClZVimlFlQWKllxlyviE70wOo4eXIT70bF2t2N8DMLWeZvuVfbCzU/DGwWYHB9/WkdIInbUNRYN8nL+LhUPiOLE8ief9+MBIkFoP8kj35UjKyefuHfRy/moSLRQ7rHL6mfNoZ4myr8HOdRWSrbQs91+PqVrrGz0WdbBgsT81XoO0UcPQhR6sreicIvd6wvVb8eYi/AAmXwNaVLNfqnMrxYX+cmiNRiRyOSiAmOTPf6W52ljxT0ZWezSrSWJa1EGXI9ohYPvzPYdKztdT1c2Zxj2dwLeWFqUuMTgtpN+FWLNyKMTziIiD2FMSchOSrBZ6mVTQo7tVQeQaBdz2Our7EO/+9SEpmDnV9nVja61mzZkhrdXp6LN7P/87eoIqHPX8MaJZvnOVPYRcZ+8dJGvq78Gv/pg/U7MeRvH8/mFKdhqnVapkwYQL/+c9/iI6OxsfHhx49evDZZ58Ze0f0ej3jx4/nhx9+IDExkWbNmjFv3jyqVq1qLCc+Pp5Bgwbx559/olKp6Ny5MzNnzsTe/s6sr2PHjjFgwAAOHDiAu7s7gwYNYtSoUY+8zY8znU5/e+mIW9TxdaZBBZdif+Ity9KztPRecpDjV5Nwtlbzg8NCyqecIV3jxNqa3xYZIAJEOjQkqe0GXI//AHu+g9N/wvkdEDIeTaPehkDwVgzcvB0Imjwi4e7eBcASqAfUs3UD95ro69Ykyb4yp7Q+/JPkwZ7rOk5eTeZmahYbTkaz4WQ0z1R04cOWVWhRzV16F0Wp+u3IFUauPkaOTk/zau7Mf6dB0WPzHhZtNsSehuz02wl5+kTy9Y/keZ6dDqlxd4LA3O9T4wzP026C/h7LXjn6gmcg8fZV+SnSnr9iXLig96FihjNf1q+FVqfn/WUHScvS8mxFVxb1aGT2hBK1SmH6m/VoP+t/nIu9xdjfTzC1S12Tv/+NJ28voB0oezUL85VqkDh58mTmzZvH0qVLCQoK4uDBg/Ts2RMnJycGDx4MwJQpU5g1axZLly4lICCAsWPHEhoayqlTp7C2NnSbd+vWjevXr7N582ays7Pp2bMnffv2ZcWKFQAkJyfTunVrQkJCmD9/PsePH6dXr144OzvTt2/fUmv/4+RKQhofrT7K3gvxJun+brY0rOBCA38XGvq7UM3TAfVjtN1TVo6Ofv85xP6L8ThYafit7n4Cjm5Dh5r11SeRbF2+eAVZ2EDIBKj1Ovw5xDDW6K+P4H/TICMRstOKOFkBJz9wDQDnCoY3oNjTkHDR8P2l3SiXduMMNL39wN4TbdUa3LAJ4J8UL2ZH+nDgIvRcfIBa5R0Z2LIKrQO9ZOst8cgt/N8Fvlx/GoDX6vnwf6/XfXTr8mUkw5X9hr2No/bClYOQk37v8+6LArauYOcB9u7gVgU8AsEzyPDVxhkAV2CwXk/5w1f5+q/TnI29xZsL9qJRKeTo9DxftRwL3m103+ONy9lbMatrfd5euI81R67ybIArXW+PO0xKy2bv7WV/ZJcVcT9K9Xbzyy+/jKenJ4sWLTKmde7cGRsbG/7zn/+g1+vx8fFhxIgRfPTRRwAkJSXh6enJkiVL6Nq1K6dPnyYwMJADBw7QqFEjADZs2EC7du24cuUKPj4+zJs3j08//ZTo6GgsLQ1d+aNHj+b333/nzJkz96xnme+uzs4wBCLpiWBXzvAoIXq9ntWHrjDxz1PcyszB1lJNaJAXp64l829sSr4P4/ZWGupXMPQyNvR3oV4FZ5PFbIui0+rISrqO7uYFNPosLF0rGMb5WRbdk3e/crQ6Bq88wl/Ho7G2UPFHmwyqbemFotexrdJIjnp3KVY5qcmJfNiyCq6urrkNgQOLYOvEO72EitoQALpWyv9w8QdNAT2yWWlwIwJiz0DcaUPgGHsGkqIKrEeCpQ+bM2qyMyeIPbpAynn48GHLyrxSx6foW95ClAC9Xs83G87w/U7DLiq9mgXwWfuaD/eDStJViAq7ExTGnszfw2ftbAjmjO6qj0mv++3v1ZaGwM/OA+w9wM4d7D1N02zLgdq8fpbEtCwmb4gwruP4UqAns9+uj5XmwSekzd1xjikbIrDSqPjtw2YE+jjy+5GrDP05nGqe9mwa9sIDX+NxVObfv8u4Uu1JbNq0KQsWLODff/+lWrVqHD16lN27dzNt2jQAIiMjiY6OJiQkxHiOk5MTjRs3JiwsjK5duxIWFoazs7MxQAQICQlBpVKxb98+OnbsSFhYGM2bNzcGiAChoaFMnjyZhIQEXFxcTOqVmZlJZuad8V8pKflvBz500ScMQUFGIqQnGALAwr7P+0lZUUGVEKj/DlRrC5r7HwMUl5LJmDXH2XLacLuikb8LU7vUxd/NDoCk9GzCLydy6FIChy8lcCQqgVuZOXd2JMDw/28Vd3tsLNVk5ejQ52TilhONZ040ntrr+OijKa+Pxk8fg58Si42Sla8e6RYuaB3KY1XOHwuXCuDke/vhZ/hq525cQ6y4dDo9Y9Yc56/j0VioFZa95kb1za+DXscRlzYc9Xrjvn9uqNTQuC8EdYSYE4bg0MnP/NfC0hZ86hseeWWmQNy/hvFPcWcMvSVXD+KSdY0uqmt0sdwKwMlEf3b/WovRGxryTPP2dGhctUTejITIKzopgx0Rsaw/ft34d/9xmxr0e6FSyQ57yE43/L5fPXQnKEy6nD+fSwBUaHL7EQxuVc3+/+Fhcba1vD3D2I8z11Po2KA8FiX0Aa5f88ociIxne0QcA1YcZu3AZmw6ZdhlpXWg9CKK+1OqQeLo0aNJTk6mRo0aqNVqtFotX331Fd26dQMgOtrwC+7paTqWwtPT03gsOjoaDw8Pk+MajQZXV1eTPAEBAfnKyD12d5A4adIkPv/88xJq5X068h/YN6/4+RUVWDkagsezmwwPWzeo3QXqdwOv2mZd/u/j1/n09xPEp2ZhqVYxvHU1+jxfyeRWspONBS9Uc+eFau6AYRB1RHQKh6ISOHIpgUOX4vFKOMzL8WFUUq7jr4rBm5uolbu6HxWMH+C1eoXruJGut8JHuYGdkolNdgLEJ0D8iYIrq7Y0BIsBL0DdruDXmCytnpupmdxIyeLGrUzibmUSl5LJjVuZ3LiVRdTNVI5eSUKlwNzXq/LsP29DZhLZ3g3Z4DoI65J4c7N3B/uWD17O3awcwLeh4ZErMwUuhcGFHYZH7EmCVJcIUl2CzPVkbfqKE1tqoA94gaDnXsW64rOGYFYIM2VrdRy6lMCOiDh2RMRyJvrOh2iVAt90qkOXZ/zu/wJ6vWHiR/QJw4esmJOGrzfP5e8lVNTgXQf8mtwJDB3KfkBUx9ewpFVJUqkUpnUxjE+MvJHKyNXH2HU2DoDWQTIeUdyfUg0SV61axfLly1mxYgVBQUGEh4czdOhQfHx86N69e6nVa8yYMQwfPtz4/OrVqwQGFryo6UPjUQMCmhtuldi4GMa3FPW9laPh0/KNcxD+Hzi6ElKuGwLNffPAuy7Ufxdqdb7r1ouppPRsJqw9yW9HDLPzano7Mv3NutTwcrxnldUqhUAfRwIdM3lX+zvELoO0c/ny6dTWZDn6k+3kj9bJH71zALgGoLgFoHapQDlLaxLSsgi7ksS5y1eJvXyOW7EXsUq7RnnlJj7KDXxuf/UkAbU2685EkEOLuYwna3KasUb7HJf0Rb9hTOlci5dOj4Ib/4KDD7fazUO7P+mebS1zrBygWmvDAwyD7CN3kXNuGxkR27DPuE4D/Um4cBIuzCXZxhf71p+gqvOm2bfMxNMnOimDnf/Gsv1MHP+cu0FKZo7xmKJAXV9nWlR3p11tb/PWQMxKM9wxyRsMxpyAjEL+Bm3dwKvOnYCwfCOwuve2dE8LFztLZndrQJf5YWy4vVezt5M1tcs7lXLNxOOqVN8dRo4cyejRo+natSsAtWvX5tKlS0yaNInu3bvj5WV4g4+JicHb29t4XkxMDPXq1QPAy8uL2NhYk3JzcnKIj483nu/l5UVMTIxJntznuXnysrKywsrqzhix5OTkB2zpfWjYw/AwV7kqhgkULT+D89sMAeOZv+D6UcNj4ydQ42VD72Kllia9Sf87G8eoX45xPSkDlQL9W1RmyIvVijfoXKeDyB1waCmcWQ+6bEO6pT3U6mS47eNiCAZV9p5YKwpFrdbl7WSDt5MNIUFegKHHLCE1i1PXkzl5LYktVw1fo24k4aFPoKrqKq+ow2ij2o+fEsMQzRqGaNZwXKnG/2xe5IRLCLbO7pSzt6KcvSXuDlYE+ThS5fh0+HcDaKyh63L0Nu7AYxgk3s3eA2q/jqb269jr9WTGnePorj9IPb2VBjnhOKVfgT8+JHvnVCxajTG8RtKzeH8ykiEhEn18JIlXzpB28xoeXuWxcCkPjj6GcbWOPoZA/jGg1+tJSMsmIjqFXWfj2H7GtLcQwNXOkhequdOiujvPV3Uv3tI2er3hg9zl/YbJJZcPFDyGEEClgXLVDZNAPIPAqxZ41jKMC5SZ+0VqUMGF0W1rGCcPtQ70lNUOxH0r1SAxLS0N1V1jRdRqNTqd4T+NgIAAvLy82Lp1qzEoTE5OZt++ffTv3x+A4OBgEhMTOXToEA0bGoKJbdu2odPpaNy4sTHPp59+SnZ2NhYWhkkUmzdvpnr16vluNT8x1Jo7PUupN+H4asMt7JjjcHKN4eFYHup2JdOrAd+fUJh9JJssLAgoZ8e3b9SloX8xfjYp0YZyDy+DxEt30n0aGILcWp1K7M3Rxc6SZlXK0azKnYk5aVk5nL6ewtmYFDSWPThurcU/bjvlzv+G5tJOauv/pXbav5CxEOxbg/+bUK2NYaLIiV/hf1MNBb36HZRvAPHxhVz9MaYoWHlU5dnXPyJHO5zVYRFc2fQdvZU/cE08D2veR7/r/1BafAyBHcvM+K0yQ6839MzGX4CESMOyRbeDQt3NC6gzDL8zCuBy+8G/BZRj6XA7aMwNHL3vfG/nfufOgJXTQ38N9Ho98alZXLyZxsUbqVy6mUrkzTTD1xuppGTkmOTP21vYoroHtcs73XsVg8xbhvGDVw7ceaTdzJ/Pzt0QAHoGGb561YJy1QqezCWKpfdzARy7ksTfJ67zRqMHuPUvnnqlOru5R48ebNmyhe+//56goCCOHDlC37596dWrF5MnTwYMy+R88803JkvgHDt2zGQJnLZt2xITE8P8+fONS+A0atTIuAROUlIS1atXp3Xr1nz88cecOHGCXr16MX369GItgfNEzY66ftQQ1B1bZRi/mIdWr5Bs5YWjTzXU5arcmX3rVhmc/cHidt+fTgvntsLhpRDxN+i1hnQrR6jzJjTsbvYYyIciJdqwJ+qxlRB9/E66tRPUeMUQJOakQ9PB0PoLwLDm5tzt57BzdC72ZfLNbn4MXLyRyicr91Dv+mr6atbhrKQaDngEQovRhp/P0xQs6rSGcXB516/M/ZpwEbJTizz9ht6RKL0Hl/EkQV0Om+wkvJR4AqySKK9KQJ1lzt0IxfA7WtQQExuX2w9XsHEhy9KZNLUDt7Rq0rK0pGbmkJqpJTUrx/B9lpbY5AxjUHjxZv5A8G4+TtY8G+BKi+oePF+1HG72hQRtOp1h/cCU64Zbx0X1EqqtwKce+D5jePg9awiURYnT6/VkZOue+q08n6j371JQqkFiSkoKY8eO5bfffiM2NhYfHx/eeustxo0bZ5yJnLuY9oIFC0hMTOS5555j7ty5VKtWzVhOfHw8AwcONFlMe9asWYUupl2uXDkGDRrExx9/XKx6Pim/ZIlpWZy8ZrhNG3ElDufLW6l3axeVlOtUVMVgR0YRZ+dZy+/meUi+cueQX2NDr2Fgh4e2XM0DizllCBaPrYaUa3fSq4TA26uMt1qfliARDEsAfb/rAgu3hPMOf9PX4i8cuL2eo2dtaDkGqrcr3u09nRYSowy/GzfPGQIsBy+o3hbcazz6W4R6vWEhZV02aLNAm2P4PivVEPSZBIIXDL3g2vwz63PpUBGtlONCjjtRek8u3X5cVTxx9qlK3SoVCK7sRoMKLigKfL/zAvN2niMjW4dKge4NyzHkWXucc+Ig+ZohIE2+BsnXDX9LqTeLsZ7mvaXqrUjEnkS94ZGAPUm3v6bobUnDinSsSNdbkYYVdnb2ODs54+bqgqerC97ubpT3KEcFT1esLTSQmWyoY0reR7Sh7inRhue3YkBXSMDp6At+z4Dvs4aA0Ku29BCKR+pJef8uLbItXzE8br9ker2e60kZxoDw5LVkTl1L5mpiwYvKdqpfnvGvBOKkTcjTk3J7d5Cb5wveFcTaGeq9DQ3eA4+aD79RJUWnhYv/M/SkZqfBy9MNPTK3PU1BYq6T15IY9nM40THR9Nb8zQeWG7HW3Q5WvOtCy0+h6u0JMak3DEHgzbO3v+YJCgsLspz9DcFm9bbg3xTU5u0qYSL1pmFdvEt7DF9Tbxiuq8s2BIK53xcWtBRBp7Lklk15ojXenMv24GiaCxFZ7lzSe3JF7042GtQqhTq+TgRXciO4shsN/V0K3UnkamI6X/91mvXHrgOG1QCGhVTlnSb+ha9bmZOZb4mrzFs3OX3hMmcvRXEr8QaOSirOpOKs3MKZW8av+VYNeFAqiztji+9JMYyDdQkA30aGgND3GeklFKXucXv/LmskSCyGx+GXLFurY+mei+yIiOPktSQS0gr+z72Cqy1BPo63H04ElXe894bvefcXvnneMJuwauid289PkKcxSATIyNYydVMEC3dH4qRPYYT9Jt7mb9Q5t4NFZ39D8JJZxKQetZVhaIJbZXCpaNjL9sJO0ObZc9rKCaqGGNbwrBpiEqAXKPk6XPrHEBRe2mNYVPx+qTSgsUHrVIFE6/JcVXkTkeXO4RRn9iQ4clnrig7T4M1CrRDoYwgKm1Ry5ZmKrvn2xr2XvRdu8vmfpzh93XDLubqnA+NfCaRpnrG1d9Pr9RyOSmT1wcusO3adW7dnEysKPFelHJ0b+FKxnB12lmrsrDTYWaiw1adikZUIaQm3A8x4w9e0eMP3mSmGntTsdMMHpLzfZ6cZZhoXtDuJlZNh/KSDFzj4GL46+pg+t/eUWfKiTHoc3r/LMgkSi6Gs/5Idu5LIqF+OmcxAVKsUqnrYE5gbDPo4EujjWOzdT55WT2uQmGvvhZuMWHWUq4npuCnJzKn4PxrHrUExBg8KOPsZtiBzq3r7a2XDVydf4237jGwtVhoVSlaqYd3GiL8Ns8jTbty5mKI29CxWb2uYTORayXDb92JuUPiPYaLIXTKcq3JMHcQvNysQkVmObDRko0GrqNErFuhUFuhVFuhVmttfLVDUGjRqFVk5Oq4lFTyswtFaQ5CPk2EZJ2/D30tld/sS2VJOq9Pz3/1RfLspgsTbH+DaBHnxafua+LneGaIRm5zBmiNXWXXwMhfi7oyDrOBqyxsNfenc0BcfZ5sHrk+hdDpDoJiVBjkZhuWyLO0e3vWEeMjK+vt3WSdBYjGU1V+y9Cwt0zZHsGh3JDo9uNhaMKhVVRpVNOyhbG3xdA9Yvh9Pe5AIkJKRzcQ/T7H6kGHcaROPHL5qosPStQKxGh9uZCokpGZxMzWLhNQs4nO/T8vi5i3D8/RsLe4OVrwU6EnrQE+CK7thpcIw2zXiL4jYkL9X0Nop//p4igq8apNZvgl7tTX4/qIHe64/+PhGXxcbYyCY+7W8s81DXyokMS2L6Zv/5T/7otDq9FhqVPRrXolAH0dWH7zCjn/j0OoM/yXbWKhpV9ubNxr58mxFV9mHW4j7UFbfvx8XEiQWQ1n8Jdtz7gaj1xwnKt5wO/C1ej6Mezmw8BmIolgkSLxj48loPllznJuphU/oKC57Kw0tqrvzUqAnLWt4GHq04yMNvYsRfxl6DnU5hlvCPg3Avyl6/6YcoTrLw5NYf/waGdmGmbKWahWtgzzp+kwF6ldwJkenR6vTk6PTGb5q9bfTdOTc9RwUqnjY42RTuj3qEdEpfP7nSfacz78kTEN/F7o08qV9HR/szby1LYQwVRbfvx8n8j/QYyYpLZuv/zrNzwcNe5Z6O1nzVcdatKoh2y6JkhUa5EVDfxc+++0Em05FY2epwdXeEhdbS9zsLHEt5OFmZ4WjjYZjV5LYdCqaTSdjiE3JZN2x66w7dh0LtUKTSm60DvLipZo98WrS3zDeMf48uNfkRpaaNYevsPLPy1yIO2msT1UPe958xo9ODXyLt3hzGVbdy4Hl7zdmw4lopm7+l7TMHF6tV543GvlS2V12EBFClA3Sk1gMZeWTyIYT1xn7x0niUgwTAd5t4s+oNtVxkHGGJUZ6Egum0+nv+3anTqfn2NUkNp2MZtOpGM7F3jI5XtfPmdaBnlR2t2ft0atsPhVDtvbOLddX6nrz5jMVaFDBWXaOEEKYpay8fz+upCfxMRCbksH4P07y9wnDXpyV3O2Y3LkOz1R8coMSUbY8yHg4lUqhnp8z9fycGdWmBufjbrH5VAybTkZz5HIiR28/8qrr60TXZyvwch1v+RAkhBClRILEMkyv17P64BW+XH+K5IwcNCqFfi9UZmCrKjIpRTy2KrvbU/kFe/q9UJnY5Ay2nI5l06loLsSl0qqGB10a+RHo41ja1RRCiKeeBIllVNTNNMb8dox/zhkGttcu78TkznXkzVM8UTwcrXm7cQXeblyhtKsihBDiLhIkllHj1p7gn3M3sdKoGNG6Gr2aBRS+S4MQQgghRAmTILGMGv9KEHCSCa8EUbGcLGYrhBBCiEdLgsQyKqCcHUt6Plva1RBCCCHEU0ruXwohhBBCiHwkSBRCCCGEEPlIkCiEEEIIIfKRIFEIIYQQQuQjQaIQQgghhMhHgkQhhBBCCJGPBIlCCCGEECIfCRKFEEIIIUQ+EiQKIYQQQoh8JEgUQgghhBD5SJAohBBCCCHykSBRCCGEEELkI0GiEEIIIYTIR4JEIYQQQgiRjwSJQgghhBCAVqtl7NixBAQEYGNjQ+XKlfniiy/Q6/XGPHq9nnHjxuHt7Y2NjQ0hISGcPXvWeDwzM5N3330XR0dHqlWrxpYtW0yu8X//938MGjTokbXpQWhKuwJCCCGEEGXB5MmTmTdvHkuXLiUoKIiDBw/Ss2dPnJycGDx4MABTpkxh1qxZLF26lICAAMaOHUtoaCinTp3C2tqaBQsWcOjQIcLCwvj77795++23iYmJQVEUIiMj+eGHHzh48GApt7R4pCdRCCGEEALYs2cPr732Gu3bt6dixYq8/vrrtG7dmv379wOGXsQZM2bw2Wef8dprr1GnTh2WLVvGtWvX+P333wE4ffo0r776KkFBQQwYMIC4uDhu3LgBQP/+/Zk8eTKOjo6l1USzSE+iGXJycsjOzgZApVKhVqvRarXodDpjntz0nJwck+5ptVqNSqUqND233FwajcZ4zeKkW1hYoNPp0Gq1xjRFUdBoNIWmF1b3p7lNuXkUvQ7Ic3sBFSgKiv7ONY3p6E1+N8pam57E10naJG2SNkmbitsmgJSUFJKTk43HrayssLKy4m5NmzZlwYIF/Pvvv1SrVo2jR4+ye/dupk2bBkBkZCTR0dGEhIQYz3FycqJx48aEhYXRtWtX6taty08//UR6ejobN27E29ubcuXKsXz5cqytrenYsWO+65ZVEiSaISwsDFtbWwAqVKhA/fr1OXbsGFFRUcY81atXp0aNGuzfv5+4uDhjer169fD392fXrl2kpKQY04ODg/Hw8GDTpk0mf1gtW7bExsaGv/76y6QO7dq1Iz09ne3btxvTNBoN7du358aNG4SFhRnTHRwcaNWqFZcvXyY8PNyY7u7uTtOmTTl79iwRERHGdGkTVK1aFYDyGZFY6rOM6det/EhX2+Offg4Vd/6DumxdCRV6kzqWtTY9ia+TtEnaJG2SNhWnTbllBwYGmtR1/PjxTJgwgbuNHj2a5ORkatSoYQxKv/rqK7p16wZAdHQ0AJ6enibneXp6Go/16tWLY8eOERgYSLly5Vi1ahUJCQmMGzeOHTt28Nlnn7Fy5UoqV67Mjz/+SPny5fPVo6xQ9HlD70esYsWKXLp0KV/6hx9+yJw5c8jIyGDEiBGsXLmSzMxMQkNDmTt3rsmLExUVRf/+/dm+fTv29vZ0796dSZMmGT/RAOzYsYPhw4dz8uRJ/Pz8+Oyzz+jRo0ex63nlyhX8/PyIjIw0vpjySe3JbFNSUhLzd17A3sGR4vYkpqYk0vf5AFxcXMpkm57E10naJG2SNkmbitOmixcvEhAQwKlTp0yCscJ6EleuXMnIkSP5v//7P4KCgggPD2fo0KFMmzaN7t27s2fPHpo1a8a1a9fw9vY2ntelSxcUReHnn3/OVyZAz549qVevHgEBAXzyySfs27ePKVOmcOLECX799dcCzykLSrUn8cCBAya/HCdOnOCll17ijTfeAGDYsGGsX7+e1atX4+TkxMCBA+nUqRP//PMPYJiF1L59e7y8vNizZw/Xr1/nvffew8LCgq+//howdA23b9+efv36sXz5crZu3cr777+Pt7c3oaGhZtVXo9FgYWFhkqZWq1Gr1QXmLayMgtxd7v2kq1QqVKr8w0wLSy+s7k9zm3LL1CsFD9fVK/nLAKXA3w0oG226V/rj+DrdK13aJG2SNkmb8qY7ODgUaxzgyJEjGT16NF27dgWgdu3aXLp0iUmTJtG9e3e8vLwAiImJMQkSY2JiqFevXoFlbt++nZMnT7Jw4UJGjhxJu3btsLOzo0uXLsyePfuedSpNpTpxxd3dHS8vL+Nj3bp1VK5cmRdeeIGkpCQWLVrEtGnTaNWqFQ0bNmTx4sXs2bOHvXv3ArBp0yZOnTrFf/7zH+rVq0fbtm354osvmDNnDllZhluF8+fPJyAggKlTp1KzZk0GDhzI66+/zvTp00uz6UIIIYQoY9LS0vIFrWq12th7GRAQgJeXF1u3bjUeT05OZt++fQQHB+crLyMjgwEDBvD9998be0Jze2azs7NNOsrKojIzuzkrK4v//Oc/9OrVC0VROHToENnZ2SaDQ2vUqEGFChWM4xrCwsKoXbu2ye3n0NBQkpOTOXnypDFP3jJy89w9hiyvzMxMkpOTjY+8YzSEEEII8WR65ZVX+Oqrr1i/fj0XL17kt99+Y9q0acbJJoqiMHToUL788kvWrl3L8ePHee+99/Dx8aFDhw75yvviiy9o164d9evXB6BZs2asWbOGY8eOMXv2bJo1a/Yom2e2MjNx5ffffycxMdE4VjA6OhpLS0ucnZ1N8uUdHBodHV3g4NHcY0XlSU5OJj09HRsbm3x1mTRpEp9//nlJNEsIIYQQj4nvvvuOsWPH8uGHHxIbG4uPjw8ffPAB48aNM+YZNWoUqamp9O3bl8TERJ577jk2bNiAtbW1SVknTpxg1apVJhNzXn/9dXbs2MHzzz9P9erVWbFixaNq2n0pM0HiokWLaNu2LT4+PqVdFcaMGcPw4cONz69evZpvZpQQQgghniwODg7MmDGDGTNmFJpHURQmTpzIxIkTiyyrVq1aJjuxgGEM5ty5c5k7d25JVPehKxNB4qVLl9iyZQtr1qwxpnl5eZGVlUViYqJJb2JMTIxx4KiXl5dxgcu8x3OP5X7NTcubx9HRscBeRMg/6ynv2kpCCCGEEE+DMjEmcfHixXh4eNC+fXtjWsOGDbGwsDAZHBoREUFUVJRxcGhwcDDHjx8nNjbWmGfz5s04Ojoae/6Cg4NNysjNU9AAUyGEEEIIYVDqQaJOp2Px4sV0797dZAq7k5MTvXv3Zvjw4Wzfvp1Dhw7Rs2dPgoODadKkCQCtW7cmMDCQd999l6NHj7Jx40Y+++wzBgwYYOwJ7NevHxcuXGDUqFGcOXOGuXPnsmrVKoYNG1Yq7RVCCCGEeByU+u3mLVu2EBUVRa9evfIdmz59OiqVis6dO5sspp1LrVazbt06+vfvT3BwMHZ2dnTv3t1knEBAQADr169n2LBhzJw5E19fXxYuXGj2GolCCCGEEE+TUt1x5XGRu+PK5cuX8fX1Le3qiIcoPj6eudvPYefoXOxzUpMT+bBlFVxdXR9exYQQQphN3r8fTKnfbhZCCCGEEGWPBIlCCCGEECIfCRKFEEIIIUQ+EiQKIYQQQoh8JEgUQgghhBD5SJAohBBCCCHykSBRCCGEEELkI0GiEEIIIYTIp9R3XBHicafT6UhISDDrHGdnZ1Qq+YwmhBCi7JIgUYgHlJGawrytN3F2cy92/uEv15cdWoQQQpRpEiQKUQKs7RzM2spPCCGEKOvkfpcQQgghhMhHgkQhhBBCCJGPBIlCCCGEECIfCRKFEEIIIUQ+EiQKIYQQQoh8JEgUQgghhBD5SJAohBBCCCHykSBRCCGEEELkI0GiEEIIIYTIR4JEIYQQQgiRjwSJQgghhBAiHwkShRBCCCFEPg8cJCYnJ/P7779z+vTpkqiPEEIIIYQoA8wOErt06cLs2bMBSE9Pp1GjRnTp0oU6derw66+/lngFhRBCCCHEo2d2kLhr1y6ef/55AH777Tf0ej2JiYnMmjWLL7/8ssQrKIQQQgghHj2zg8SkpCRcXV0B2LBhA507d8bW1pb27dtz9uzZEq+gEEIIIYR49MwOEv38/AgLCyM1NZUNGzbQunVrABISErC2ti7xCgohhBBCiEdPY+4JQ4cOpVu3btjb2+Pv70+LFi0Aw23o2rVrl3T9hBBCCCFEKTA7SPzwww959tlnuXz5Mi+99BIqlaEzslKlSjImUQghhBDiCXFfS+A0atSIjh07Ym9vb0xr3749zZo1M7usq1ev8s477+Dm5oaNjQ21a9fm4MGDxuN6vZ5x48bh7e2NjY0NISEh+cY+xsfH061bNxwdHXF2dqZ3797cunXLJM+xY8d4/vnnsba2xs/PjylTpphdVyGEEEKIp4XZPYlarZYlS5awdetWYmNj0el0Jse3bdtW7LISEhJo1qwZLVu25O+//8bd3Z2zZ8/i4uJizDNlyhRmzZrF0qVLCQgIYOzYsYSGhnLq1CnjGMhu3bpx/fp1Nm/eTHZ2Nj179qRv376sWLECMKzl2Lp1a0JCQpg/fz7Hjx+nV69eODs707dvX3N/BEIIIYQQTzyzg8QhQ4awZMkS2rdvT61atVAU5b4vPnnyZPz8/Fi8eLExLSAgwPi9Xq9nxowZfPbZZ7z22msALFu2DE9PT37//Xe6du3K6dOn2bBhAwcOHKBRo0YAfPfdd7Rr145vv/0WHx8fli9fTlZWFj/++COWlpYEBQURHh7OtGnTJEgUQgghhCiA2UHiypUrWbVqFe3atXvgi69du5bQ0FDeeOMNdu7cSfny5fnwww/p06cPAJGRkURHRxMSEmI8x8nJicaNGxMWFkbXrl0JCwvD2dnZGCAChISEoFKp2LdvHx07diQsLIzmzZtjaWlpzBMaGsrkyZNJSEgw6bkEyMzMJDMz0/g8JSXlgdsqhBBCCPE4MXtMoqWlJVWqVCmRi1+4cIF58+ZRtWpVNm7cSP/+/Rk8eDBLly4FIDo6GgBPT0+T8zw9PY3HoqOj8fDwMDmu0WhwdXU1yVNQGXmvkdekSZNwcnIyPgIDA0ugtUIIIYQQjw+zexJHjBjBzJkzmT179gPdagbQ6XQ0atSIr7/+GoD69etz4sQJ5s+fT/fu3R+o7AcxZswYhg8fbnx+9epVCRRFidHpdCQkJJh9nrOzs3E1ASGEEOJhMztI3L17N9u3b+fvv/8mKCgICwsLk+Nr1qwpdlne3t75gq+aNWsa94D28vICICYmBm9vb2OemJgY6tWrZ8wTGxtrUkZOTg7x8fHG8728vIiJiTHJk/s8N09eVlZWWFlZGZ8nJycXu01C3EtGagrztt7E2c3drHOGv1zfuNuREEII8bCZHSQ6OzvTsWPHErl4s2bNiIiIMEn7999/8ff3BwyTWLy8vNi6dasxKExOTmbfvn30798fgODgYBITEzl06BANGzYEDDOsdTodjRs3Nub59NNPyc7ONga1mzdvpnr16vnGIwrxKFjbOWDn6Fza1RBCCCEKZXaQmHcm8oMaNmwYTZs25euvv6ZLly7s37+fBQsWsGDBAgAURWHo0KF8+eWXVK1a1bgEjo+PDx06dAAMPY9t2rShT58+zJ8/n+zsbAYOHEjXrl3x8fEB4O233+bzzz+nd+/efPzxx5w4cYKZM2cyffr0EmuLEEIIIcSTxOwgMVdcXJyxF7B69eq4uxf/1lmuZ555ht9++40xY8YwceJEAgICmDFjBt26dTPmGTVqFKmpqfTt25fExESee+45NmzYYLJP9PLlyxk4cCAvvvgiKpWKzp07M2vWLONxJycnNm3axIABA2jYsCHlypVj3LhxsvyNEEIIIUQhFL1erzfnhNTUVAYNGsSyZcuMC2mr1Wree+89vvvuO2xtbR9KRUvTlStX8PPz4/Lly/j6+pZ2dcRDFB8fz9zt58y6FRx39RIqCyvcPPKPby2J/ACpyYl82LKKjEkUQggzyPv3gzF7quTw4cPZuXMnf/75J4mJiSQmJvLHH3+wc+dORowY8TDqKIQQQgghHjGzbzf/+uuv/PLLL7Ro0cKY1q5dO2xsbOjSpQvz5s0ryfoJIYQQQohSYHZPYlpaWr6FqQE8PDxIS0srkUoJIYQQQojSZXaQGBwczPjx48nIyDCmpaen8/nnnxMcHFyilRNCCCGEEKXD7NvNM2fOJDQ0FF9fX+rWrQvA0aNHsba2ZuPGjSVeQSGEEEII8eiZHSTWqlWLs2fPsnz5cs6cOQPAW2+9Rbdu3bCxsSnxCgohhBBCiEfvvtZJtLW1pU+fPiVdFyGEEEIIUUYUK0hcu3Ytbdu2xcLCgrVr1xaZ99VXXy2RigkhhBBCiNJTrCCxQ4cOREdH4+HhYdwOryCKoqDVakuqbkIIIYQQopQUK0jM3Vnl7u+FEEIIIcSTyewlcJYtW0ZmZma+9KysLJYtW1YilRJCCCGEEKXL7CCxZ8+eJCUl5UtPSUmhZ8+eJVIpIYQQQghRuswOEvV6PYqi5Eu/cuUKTk5OJVIpIYQQQghRuoq9BE79+vVRFAVFUXjxxRfRaO6cqtVqiYyMpE2bNg+lkkIIIYQQ4tEqdpCYO6s5PDyc0NBQ7O3tjccsLS2pWLEinTt3LvEKCiGEEEKIR6/YQeL48eMBqFixIl27dsXKyuqhVUoIIYQQQpQus8ckBgYGEh4eni993759HDx4sCTqJIQQQgghSpnZQeKAAQO4fPlyvvSrV68yYMCAEqmUEEIIIURpuHr1Ku+88w5ubm7Y2NhQu3Ztk04wvV7PuHHj8Pb2xsbGhpCQEM6ePWs8npmZybvvvoujoyPVqlVjy5YtJuX/3//9H4MGDXpk7XkQZgeJp06dokGDBvnS69evz6lTp0qkUkIIIYQQj1pCQgLNmjXDwsKCv//+m1OnTjF16lRcXFyMeaZMmcKsWbOYP38++/btw87OjtDQUDIyMgBYsGABhw4dIiwsjL59+/L222+j1+sBiIyM5IcffuCrr74qlfaZq9hjEnNZWVkRExNDpUqVTNKvX79uMuNZCCGEEOJxMnnyZPz8/Fi8eLExLSAgwPi9Xq9nxowZfPbZZ7z22muAYZMRT09Pfv/9d7p27crp06d59dVXCQoKolKlSowcOZIbN27g7u5O//79mTx5Mo6Ojo+8bffD7KiudevWjBkzhj/++MO4LmJiYiKffPIJL730UolXsCzJyckhOzsbAJVKhVqtRqvVmmxVmJuek5Nj/OQAoFarUalUhabnlpsrN+DOyckpVrqFhQU6nc5k72xFUdBoNIWmF1b3p7lNuXkUvQ64k65HBYqCojfdm1yP6va/epNj+tud9Aqm21jqFXUB+RX0igr0+rvy56brUKEz/v7J6yRtkjZJm6RNxW8TGDb8SE5ONh63srIqcALu2rVrCQ0N5Y033mDnzp2UL1+eDz/8kD59+gCGnsDo6GhCQkKM5zg5OdG4cWPCwsLo2rUrdevW5aeffiI9PZ2NGzfi7e1NuXLlWL58OdbW1nTs2DHfdcsqs4PEb7/9lubNm+Pv70/9+vUBw7I4np6e/PTTTyVewbIkLCwMW1tbACpUqED9+vU5duwYUVFRxjzVq1enRo0a7N+/n7i4OGN6vXr18Pf3Z9euXaSkpBjTg4OD8fDwYNOmTSZ/WC1btsTGxoa//vrLpA7t2rUjPT2d7du3G9M0Gg3t27fnxo0bhIWFGdMdHBxo1aoVly9fNpls5O7uTtOmTTl79iwRERHGdGkTVK1aFYDyGZFY6rOM6det/EhX2+Offg5VnkDusnUl1EBD+0RITzSmR9pUQ6PPwS/jgjFNh4qLttVx0uiokSd/lmLJFZvKOGgTcc+KNuZPU9kRbV0Bl+ybVNLcICws5r7a9CS+TtImaZO0SdpUnDbllh0YGGhS1/HjxzNhwgTuduHCBebNm8fw4cP55JNPOHDgAIMHD8bS0pLu3bsTHW34P9rT09PkPE9PT+OxXr16cezYMQIDAylXrhyrVq0iISGBcePGsWPHDj777DNWrlxJ5cqV+fHHHylfvny+epQVij5v6F1MqampLF++nKNHj2JjY0OdOnV46623sLCweBh1LHVXrlzBz8+PyMhI44spn9SezDYlJSUxf+cF7B0cKW5PYty1S2gsrHB19zDNT8E9iXFXL96V/949iekpibz/fCVcXFzkdZI2SZukTdKmYrbp4sWLBAQEcOrUKZNgrLCeREtLSxo1asSePXuMaYMHD+bAgQOEhYWxZ88emjVrxrVr1/D29jbm6dKlC4qi8PPPP+crEwxbGterV4+AgAA++eQT9u3bx5QpUzhx4gS//vprgeeUBfc1iNDOzo6+ffuWdF3KPI1Gky8QVqvVqNXqAvMWVkZBCguwzUlXqVSoVPnnIhWWXljdn+Y25ZapVwqe02W4XXw3BR1Kgcf0mJFfUQrOr6jQocr3+/c0v073Spc2SZukTdKmvOkODg7FGgfo7e2dr9exZs2axkDOy8sLgJiYGJMgMSYmhnr16hVY5vbt2zl58iQLFy5k5MiRtGvXDjs7O7p06cLs2bPvWafSVKwgce3atbRt2xYLCwvWrl1bZN5XX321RComhBBCCPEoNWvWzOQ2N8C///6Lv78/YJjE4uXlxdatW41BYXJyMvv27aN///75ysvIyGDAgAEsX77c2BOa2+OZnZ1t0otaFhUrSOzQoQPR0dF4eHgYt+criKIoZb7BQgghhBAFGTZsGE2bNuXrr7+mS5cu7N+/nwULFrBgwQLAEOcMHTqUL7/8kqpVqxIQEMDYsWPx8fEpMD764osvaNeunXEOR7NmzRg5ciQ9e/Zk9uzZNGvW7FE2z2zFChLz3v/P+70QQgghxJPimWee4bfffmPMmDFMnDiRgIAAZsyYQbdu3Yx5Ro0aRWpqKn379iUxMZHnnnuODRs2YG1tbVLWiRMnWLVqlcnEnNdff50dO3bw/PPPU716dVasWPGomnZf7mviytMmd+LK5cuX8fX1Le3qiIcoPj6eudvPYefoXOxz4q5eQmVhhZuH10PJD5CanMiHLavg6upa7HOEEOJpJ+/fD6ZYPYmzZs0qdoGDBw++78oIIYQQQoiyoVhB4vTp002ex8XFkZaWhrOzM2BYTNvW1hYPDw8JEoUQQgghSoFWq2XJkiVs3bqV2NjYfEMEt23bZlZ5xQoSIyMjjd+vWLGCuXPnsmjRIqpXrw5AREQEffr04YMPPjDr4kIIIYQQomQMGTKEJUuW0L59e2rVqoWiKA9UXsGLwRVh7NixfPfdd8YAEQwrnk+fPp3PPvvMrLImTJiAoigmjxo1ahiP504dd3Nzw97ens6dOxMTE2NSRlRUFO3btzf2ZI4cOTLfQp47duygQYMGWFlZUaVKFZYsWWJus4UQQgghyrSVK1eyatUqfv75Z2bMmMH06dNNHuYyezHt69ev5wvCwNDFeXcAVxxBQUFs2bLlToXyLIg5bNgw1q9fz+rVq3FycmLgwIF06tSJf/75x3jN9u3b4+XlxZ49e7h+/TrvvfceFhYWfP3114ChF7R9+/b069eP5cuXs3XrVt5//328vb0JDQ01u75CPA50Oh2JiYlmn+fs7FzgwrZCCCHKPktLS6pUqVJi5ZkdJL744ot88MEHLFy4kAYNGgBw6NAh+vfvb7LhdbEroNEYVzDPKykpiUWLFrFixQpatWoFwOLFi6lZsyZ79+6lSZMmbNq0iVOnTrFlyxY8PT2pV68eX3zxBR9//DETJkzA0tKS+fPnExAQwNSpUwHDyum7d+9m+vTpEiSKJ1ZiYiLT1h3B2s6h2OdkpKYw/OX6MoNaCCEeUyNGjGDmzJnMnj37gW81w30EiT/++CPdu3enUaNGxq13cnJyCA0NZeHChWZX4OzZs/j4+GBtbU1wcDCTJk2iQoUKHDp0iOzsbJPAs0aNGlSoUIGwsDCaNGlCWFgYtWvXNtloOzQ0lP79+3Py5Enq169PWFhYvuA1NDSUoUOHFlqnzMxMMjMzjc/zbnguxOPC2s7BrKV8hBBCPN52797N9u3b+fvvvwkKCsq3ReKaNWvMKs/sINHd3Z2//vqLf//9lzNnzgCG4K1atWrmFkXjxo1ZsmQJ1atX5/r163z++ec8//zznDhxgujoaCwtLY0zqHN5enoSHR0NQHR0tEmAmHs891hReZKTk0lPT8fGxiZfvSZNmsTnn39udnuEEEIIIUqLs7MzHTt2LLHyzA4Sc1WsWBG9Xk/lypUL3Vj7Xtq2bWv8vk6dOjRu3Bh/f39WrVpVYPD2qIwZM4bhw4cbn1+9ejXfht9CCCGEEGXJ4sWLS7Q8s0eop6Wl0bt3b2xtbQkKCiIqKgqAQYMG8c033zxQZZydnalWrRrnzp3Dy8uLrKysfIPvY2JijGMYvby88k2WyX1+rzyOjo6FBqJWVlY4OjoaHw4OxR/XJYQQQghRmuLi4ti9eze7d+8mLi7uvssxO0gcM2YMR48eZceOHSb7FIaEhPDzzz/fd0UAbt26xfnz5/H29qZhw4ZYWFiwdetW4/GIiAiioqIIDg4GIDg4mOPHjxMbG2vMs3nzZhwdHY09f8HBwSZl5ObJLUMIIYQQ4kmQmppKr1698Pb2pnnz5jRv3hwfHx969+5NWlqa2eWZHST+/vvvzJ49m+eee85k5kxQUBDnz583q6yPPvqInTt3cvHiRfbs2UPHjh1Rq9W89dZbODk50bt3b4YPH8727ds5dOgQPXv2JDg4mCZNmgDQunVrAgMDeffddzl69CgbN27ks88+Y8CAAVhZWQHQr18/Lly4wKhRozhz5gxz585l1apVDBs2zNymCyGEEEKUWcOHD2fnzp38+eefJCYmkpiYyB9//MHOnTsZMWKE2eWZPZgwLi4ODw+PfOmpqalmT7e+cuUKb731Fjdv3sTd3Z3nnnuOvXv34u7uDhi2A1SpVHTu3JnMzExCQ0OZO3eu8Xy1Ws26devo378/wcHB2NnZ0b17dyZOnGjMExAQwPr16xk2bBgzZ87E19eXhQsXyvI3QgghhHii/Prrr/zyyy+0aNHCmNauXTtsbGzo0qUL8+bNM6s8s4PERo0asX79egYNGgRgDAwXLlxo9i3clStXFnnc2tqaOXPmMGfOnELz+Pv789dffxVZTosWLThy5IhZdRNCCCGEeJykpaXlW9EFwMPD475uN5sdJH799de0bduWU6dOkZOTw8yZMzl16hR79uxh586dZldACCGEEEI8uODgYMaPH8+yZcuM80bS09P5/PPP72suhtlB4nPPPcfRo0eZNGkStWvXZtOmTTRo0MC4sLUQQgghhHj0Zs6cSWhoKL6+vtStWxeAo0ePYm1tzcaNG80uz6wgMTs7mw8++ICxY8fyww8/mH0xIYQQQgjxcNSqVYuzZ8+yfPly44Ynb731Ft26dbuv9afNChItLCz49ddfGTt2rNkXEkIIIYQQD5etrS19+vQpkbLMvt3coUMHfv/9d1lCRgghhBCilK1du5a2bdtiYWHB2rVri8z76quvmlW22UFi1apVmThxIv/88w8NGzbEzs7O5PjgwYPNLVII8RjS6XT5dkQqDmdnZ1Qqs5doFUIIUYAOHToQHR2Nh4cHHTp0KDSfoihotVqzyjY7SFy0aBHOzs4cOnSIQ4cO5auABIlCPB0SExOZtu4I1nbF37YyIzWF4S/Xx9XV9SHWTAghnh46na7A70uC2UFiZGRkiVZACHFvOp2OhISEYudPSEgAvf4h1sjA2s4BO0fnh34dIYQQ97Zs2TLefPNN465zubKysli5ciXvvfeeWeWZHSTmpb/9JmTuTitCCPNkpKYwb+tNnN3ci5U/IeYqNk5u2N07qxBCiCdEz549adOmTb6d8VJSUujZs6fZQeJ9DQxatGgRtWrVwtraGmtra2rVqsXChQvvpyghRDHl9toV52Fla1/a1RVCCPGI6fX6Ajvurly5gpOTk9nlmd2TOG7cOKZNm8agQYOMq3eHhYUxbNgwoqKiTPZNFkIIIYQQD1f9+vVRFAVFUXjxxRfRaO6Ed1qtlsjISNq0aWN2uWYHifPmzeOHH37grbfeMqa9+uqr1KlTh0GDBkmQKIQQQgjxCOXOag4PDyc0NBR7+zt3kywtLalYsSKdO3c2u1yzg8Ts7GwaNWqUL71hw4bk5OSYXQEhhBBCCHH/xo8fD0DFihV58803jfs2PyizxyS+++67zJs3L1/6ggUL6NatW4lUSgghhBBCmKd79+5YW1uTlZXFlStXiIqKMnmY675mNy9atIhNmzbRpEkTAPbt20dUVBTvvfcew4cPN+abNm3a/RQvhBBCCCHMdPbsWXr16sWePXtM0nMntDz0xbRPnDhBgwYNADh//jwA5cqVo1y5cpw4ccKYT5bFEUIIIYR4dHr06IFGo2HdunV4e3s/cCxmdpC4ffv2B7qgEEIIIYQoeeHh4Rw6dIgaNWqUSHmygaoQQgghxBMgMDCQGzdulFh5EiQKIYQQQjwBJk+ezKhRo9ixYwc3b94kOTnZ5GGuB9qWTwghhBBClA0hISEAvPjiiybpj2ziihCPE51OR2JiYrHzJyQkwO09yYUQQojHSUnPGylWkNigQQO2bt2Ki4sLEydO5KOPPsLW1rZEKyLEw5CYmMi0dUewtnMoVv6EmKvYOLlh95DrJYQQQpS0F154oUTLK9aYxNOnT5OamgrA559/zq1bt0q0EkI8TNZ2Dtg5OhfrYWVrf+8ChRBCiDLqf//7H++88w5Nmzbl6tWrAPz000/s3r3b7LKK1ZNYr149evbsyXPPPYder+fbb7812Rcwr3HjxpldCSGEEEII8WB+/fVX3n33Xbp168bhw4fJzMwEICkpia+//pq//vrLrPKKFSQuWbKE8ePHs27dOhRF4e+//0ajyX+qoigSJAohhBBClIIvv/yS+fPn895777Fy5UpjerNmzfjyyy/NLq9YQWL16tWNF1OpVGzduhUPDw+zLyaEEEIIIR6OiIgImjdvni/dycnJrEmcucxeJ1Gn00mAKIQQQghRxnh5eXHu3Ll86bt376ZSpUpml3dfS+CcP3+eGTNmcPr0acCwwveQIUOoXLny/RQnhBBCCCEeUJ8+fRgyZAg//vgjiqJw7do1wsLC+Oijjxg7dqzZ5ZkdJG7cuJFXX32VevXq0axZMwD++ecfgoKC+PPPP3nppZfMroQQQgghhHgwo0ePRqfT8eKLL5KWlkbz5s2xsrLio48+YtCgQWaXZ3aQOHr0aIYNG8Y333yTL/3jjz+WIFEIIYQQohQoisKnn37KyJEjOXfuHLdu3SIwMLDQFWnuxewxiadPn6Z379750nv16sWpU6fuqxIA33zzDYqiMHToUGNaRkYGAwYMwM3NDXt7ezp37kxMTIzJeVFRUbRv3x5bW1s8PDwYOXIkOTk5Jnl27NhBgwYNsLKyokqVKixZsuS+6ymEEEIIURb16tWLlJQULC0tCQwM5Nlnn8Xe3p7U1FR69epldnlmB4nu7u6Eh4fnSw8PD7/vCS0HDhzg+++/p06dOibpw4YN488//2T16tXs3LmTa9eu0alTJ+NxrVZL+/btycrKYs+ePSxdupQlS5aYLMMTGRlJ+/btadmyJeHh4QwdOpT333+fjRs33lddhRBCCCHKoqVLl5Kenp4vPT09nWXLlpldntm3m/v06UPfvn25cOECTZs2BQxjEidPnszw4cPNrsCtW7fo1q0bP/zwg8kaPklJSSxatIgVK1bQqlUrABYvXkzNmjXZu3cvTZo0YdOmTZw6dYotW7bg6elJvXr1+OKLL/j444+ZMGEClpaWzJ8/n4CAAKZOnQpAzZo12b17N9OnTyc0NNTs+gohhBBClCXJycno9Xr0ej0pKSlYW1sbj2m1Wv7666/76sgzO0gcO3YsDg4OTJ06lTFjxgDg4+PDhAkTGDx4sNkVGDBgAO3btyckJMQkSDx06BDZ2dmEhIQY02rUqEGFChUICwujSZMmhIWFUbt2bTw9PY15QkND6d+/PydPnqR+/fqEhYWZlJGbJ+9t7btlZmYaVykHSElJMbtdQgghhBCPgrOzM4qioCgK1apVy3dcURQ+//xzs8s1O0hUFIVhw4YxbNgwY/Dk4OBg9oUBVq5cyeHDhzlw4EC+Y9HR0VhaWuLs7GyS7unpSXR0tDFP3gAx93jusaLyJCcnk56ejo2NTb5rT5o06b5+mEI8znQ6HQkJCcXOn5CQAHr9Q6yREEKI4ti+fTt6vZ5WrVrx66+/4urqajxmaWmJv78/Pj4+Zpd7X+sk5rrf4BDg8uXLDBkyhM2bN5t0i5YFY8aMMbl1fvXqVQIDA0uxRkI8fBmpKczbehNnN/di5U+IuYqNkxt2D7leQgghivbCCy8AhnkYFSpUQFGUEinX7IkrJeXQoUPExsbSoEEDNBoNGo2GnTt3MmvWLDQaDZ6enmRlZeXbRiYmJgYvLy/AsLL43bOdc5/fK4+jo2OBvYgAVlZWODo6Gh8PEgwL8TixtnPAztG5WA8r2/tbUkEIIcTD4e/vz+7du3nnnXdo2rQpV69eBeCnn35i9+7dZpdXakHiiy++yPHjxwkPDzc+GjVqRLdu3YzfW1hYsHXrVuM5ERERREVFERwcDEBwcDDHjx8nNjbWmGfz5s04Ojoae/6Cg4NNysjNk1uGEEIIIcST4NdffyU0NBQbGxsOHz5snF+RlJTE119/bXZ5pRYkOjg4UKtWLZOHnZ0dbm5u1KpVCycnJ3r37s3w4cPZvn07hw4domfPngQHB9OkSRMAWrduTWBgIO+++y5Hjx5l48aNfPbZZwwYMAArKysA+vXrx4ULFxg1ahRnzpxh7ty5rFq1imHDhpVW04UQQgghStyXX37J/Pnz+eGHH7CwsDCmN2vWjMOHD5tdnllBYnZ2Ni+++CJnz541+0L3Y/r06bz88st07tyZ5s2b4+XlxZo1a4zH1Wo169atQ61WExwczDvvvMN7773HxIkTjXkCAgJYv349mzdvpm7dukydOpWFCxfK8jdCCCGEeKJERETQvHnzfOlOTk75hu8Vh1kTVywsLDh27JjZFymuHTt2mDy3trZmzpw5zJkzp9Bz/P39+euvv4ost0WLFhw5cqQkqiiEEEIIUSZ5eXlx7tw5KlasaJK+e/duKlWqZHZ5Zt9ufuedd1i0aJHZFxJCCCGEEA9Pnz59GDJkCPv27UNRFK5du8by5csZMWIE/fv3N7s8s5fAycnJ4ccff2TLli00bNgQOzvTBTCmTZtmdiWEEEIIIcSDGT16NDqdjhdffJG0tDSaN2+OlZUVI0eO5P333ze7PLODxBMnTtCgQQMA/v33X5NjJbUujxBCCCGEMI+iKHz66aeMHDmSc+fOcevWLQIDA/n+++8JCAgwbjRSXGYHidu3bzf3FCEKpNPpzB5I6+zsjEpVapPyhRBCiDInMzOTCRMmsHnzZmPPYYcOHVi8eDEdO3ZErVbf16ou973jyrlz5zh//jzNmzfHxsYGvV4vPYnCLImJiUxbdwRru+ItVp6ekkSv5yvh4uJS7GvI1nFCCCGedOPGjeP7778nJCSEPXv28MYbb9CzZ0/27t3L1KlTeeONN1Cr1WaXa3aQePPmTbp06cL27dtRFIWzZ89SqVIlevfujYuLC1OnTjW7EuLplbvDR3GkpSQxb+uZYm8bB7J1nBBCiCff6tWrWbZsGa+++ionTpygTp065OTkcPTo0QfqwDP7vt2wYcOwsLAgKioKW1tbY/qbb77Jhg0b7rsiQhSHOdvGydZxQgghngZXrlyhYcOGANSqVQsrKyuGDRv2wHd4ze5J3LRpExs3bsTX19ckvWrVqly6dOmBKiOEEEIIIcyj1WqxtLQ0PtdoNNjbP3gnidk9iampqSY9iLni4+ONW+EJIYQQQjzuvvnmGxRFYejQoca0jIwMBgwYgJubG/b29nTu3JmYmBjj8fj4eF555RXs7e2pX79+vs08BgwYUOJD8/R6PT169KBTp0506tSJjIwM+vXrZ3ye+zCX2UHi888/z7Jly4zPFUVBp9MxZcoUWrZsaXYFhBBCCCHKmgMHDvD9999Tp04dk/Rhw4bx559/snr1anbu3Mm1a9dMArCvvvqKlJQUDh8+TIsWLejTp4/x2N69e9m3b59J0FkSunfvjoeHB05OTjg5OfHOO+/g4+NjfJ77MJfZt5unTJnCiy++yMGDB8nKymLUqFGcPHmS+Ph4/vnnH7MrIIQQQghRlty6dYtu3brxww8/8OWXXxrTk5KSWLRoEStWrKBVq1YALF68mJo1a7J3716aNGnC6dOn6dq1K9WqVaNv374sWLAAgOzsbPr168fChQvva6ZxURYvXlyi5eUyO0isVasW//77L7Nnz8bBwYFbt27RqVMnBgwYgLe398OoY5mRk5NDdnY2ACqVCrVajVarRafTGfPkpufk5KDPs/SKWq1GpVIVmp5bbi6NRmO8ZnHSLSws0Ol0aLVaY5qiKGg0mkLTC6v7o2pTTk4OKnTGJWoUdCb59Yoa9Hpjuho9Crevkyf9dqvQKyrQ6+7kMaQavup1kCddjwKKKl964flVoCgo+js/R2M6elToTY7pb3fSF9imfPlz6154m3LbbjjHkF5Um/Lmv1P3ottk/PkW9nrc1abivR6m6bnfl/bv3r3SH8e/J2mTtEnaVHCbAFJSUkhOTjYet7KyKnKI3IABA2jfvj0hISEmQeKhQ4fIzs4mJCTEmFajRg0qVKhAWFgYTZo0oW7dumzbto3333+fjRs3Gnsip0yZQosWLWjUqFGh1y1r7mudRCcnJz799NOSrkuZFxYWZhyPWaFCBerXr8+xY8eIiooy5qlevTo1atRg//79xMXFGdPr1auHv78/u3btIiUlxZgeHByMh4cHmzZtMvnDatmyJTY2Nvz1118mdWjXrh3p6ekmi5prNBrat2/PjRs3CAsLM6Y7ODjQqlUrLl++THh4uDHd3d2dpk2bcvbsWSIiIozppdGmIA1E4oRGn4NfxgVjug4VF22rY6NLxTvzMgABLpCuzeQ63jhoE3HPurNyfJrKjmjrCrhk38Ql54Yx3c5WzaVsa9yyonHUJhnTEzTlSLB0xzPzCra6VGO63tKSm3oonxGJpT7LmH7dyo90tT3+6ecMge1tl60roQYa2idCeqIxPdKmWqFtctLoqJEnf5ZiyRWbykW2qZJLOpAO6Ykkq524YeVTZJsC8uSPs/QiReNyzzYFuACkc1nvSo6iISDddEelu9sU4AJafTqX8DZ5nYpqU4rKMLC6uL971apVw9PTk+PHj5ssvF61alW8vLw4dOgQaWlpxvRatWrh4uJCWFjYU/n3JG2SNkmbTNuUW3ZgYKBJXcePH8+ECRMoyMqVKzl8+DAHDhzIdyw6OhpLS0ucnZ1N0j09PY27mYwePZr+/ftTuXJlKlasyKJFizh79ixLly4lLCyMfv36sWnTJho1asQPP/xwX7eBHxVFrzd/peGEhAQWLVrE6dOnAcMPv2fPnri6upZ4BcuCK1eu4OfnR2RkJOXLlwfkk1pJtCkhIYGF/7uAjYNhcex79STevHYZxcIKFw/vYvckxl27jGJhTTl3D4rTk1h4/sJ7EuOuXUJjYYWru4dp/kLaFHf14l35792TGH8tCsV4zr17Em/myV/cnkTjz9fdq+C639Wm4r0epumpKUn0b1kNJyenYv3uJSUlMeOvo9jY2ZF3IYfb/aQmATuADoWM1FsMblPbZNH1p+HvSdokbZI25a/7xYsXCQgI4NSpU8b3byi8J/Hy5cs0atSIzZs3G3sAW7RoQb169ZgxYwYrVqygZ8+eZGZmmpz37LPP0rJlSyZPnpyvTIBWrVoxZMgQLl26xLp161i/fj19+vTBzc2tTK8vbXZP4q5du3jllVdwcnIydpnOmjWLiRMn8ueff9K8efMSr2RZodFosLCwMElTq9UFji3I/WMpbvrd5d5PukqlKnDLusLSC6v7o2qTRqNBdztQAdBTwBgNRTGma1FQ5YYKedJN86vI+6lHj4IChoClAHen3zt/QeNIFHQoBR4rsI6F5S+iTbltz3tOUW0yL/9dP9+iXo886cV7PUzTcwPN4v7uqVQqrO0csC3mguu3L1rg3yo82X9PxUmXNkmb4Olsk4ODA46OjgXmyevQoUPExsbSoEEDY5pWq2XXrl3Mnj2bjRs3kpWVRWJioklvYkxMDF5eXgWWuXjxYpydnXnttdfo1KkTHTp0wMLCgjfeeINx48bds06lyewgccCAAbz55pvMmzfP+EJptVo+/PBDBgwYwPHjx0u8kkIIIYQQD9uLL76YL47p2bMnNWrU4OOPP8bPzw8LCwu2bt1K586dAYiIiCAqKorg4OB85cXFxTFx4kR2794NGOKl3J7Z7Oxsk17UssjsIPHcuXP88ssvJpG8Wq1m+PDhJkvjCCHE3XQ6nWE/7WKSvbeFEI+Sg4MDtWrVMkmzs7PDzc3NmN67d2+GDx+Oq6srjo6ODBo0iODgYJo0aZKvvKFDhzJixAjjre5mzZrx008/0bp1axYsWECzZs0efqMegNlBYoMGDTh9+jTVq1c3ST99+jR169YtsYoJIZ48GakpzNt6s9j7b8ve20KIsmb69OmoVCo6d+5MZmYmoaGhzJ07N1++jRs3cu7cOX766Sdj2sCBAzl48CCNGzfm2WefZfz48Y+y6mYrVpB47Ngx4/eDBw9myJAhnDt3zhg17927lzlz5vDNN988nFoKIZ4YuftvF0daStK9MwkhxEO0Y8cOk+fW1tbMmTOHOXPmFHleaGgooaGhJmm2trasWrWqpKv40BQrSKxXrx6KopjMHBo1alS+fG+//TZvvvlmydVOCCGEEEKUimIFiZGRkQ+7HkIIIYQQogwpVpDo7+//sOshhBBCCCHKkPvaceXatWvs3r2b2NhYk0UtwTBmUQghhBBCPN7MDhKXLFnCBx98gKWlJW5ubijKnX0QFEWRIFEIIYQQ4glgdpA4duxYxo0bx5gxYwpcJV0IIYQQQjz+zI7y0tLS6Nq1qwSIQgghhBBPMLMjvd69e7N69eqHURchhBBCCFFGmH27edKkSbz88sts2LCB2rVr59vIe9q0aSVWOSGEEEIIUTruK0jcuHGjcVu+uyeuCCGEEEKIx5/ZQeLUqVP58ccf6dGjx0OojhBCCCGEKAvMHpNoZWVFs2bNHkZdhBBCCCFEGWF2kDhkyBC+++67Ern4vHnzqFOnDo6Ojjg6OhIcHMzff/9tPJ6RkcGAAQNwc3PD3t6ezp07ExMTY1JGVFQU7du3x9bWFg8PD0aOHElOTo5Jnh07dtCgQQOsrKyoUqUKS5YsKZH6CyHKHp1OR0JCAvHx8cV+3L0pgBBCiPu43bx//362bdvGunXrCAoKyjdxZc2aNcUuy9fXl2+++YaqVaui1+tZunQpr732GkeOHCEoKIhhw4axfv16Vq9ejZOTEwMHDqRTp078888/AGi1Wtq3b4+Xlxd79uzh+vXrvPfee1hYWPD1118Dhn2n27dvT79+/Vi+fDlbt27l/fffx9vbm9DQUHObL4Qo4zJSU5i39SbObu7Fzj/85fq4uro+5JoJIcTjxewg0dnZmU6dOpXIxV955RWT51999RXz5s1j7969+Pr6smjRIlasWEGrVq0AWLx4MTVr1mTv3r00adKETZs2cerUKbZs2YKnpyf16tXjiy++4OOPP2bChAlYWloyf/58AgICmDp1KgA1a9Zk9+7dTJ8+XYJEIZ5Q1nYO2Dk6l3Y1hBDisWZ2kLh48eKHUQ+0Wi2rV68mNTWV4OBgDh06RHZ2NiEhIcY8NWrUoEKFCoSFhdGkSRPCwsKoXbs2np6exjyhoaH079+fkydPUr9+fcLCwkzKyM0zdOjQQuuSmZlJZmam8XlKSkrJNVQIIYQQ4jFQ6tumHD9+HHt7e6ysrOjXrx+//fYbgYGBREdHY2lpibOzs0l+T09PoqOjAYiOjjYJEHOP5x4rKk9ycjLp6ekF1mnSpEk4OTkZH4GBgSXRVCGEEEKIx4bZPYkBAQFFrod44cIFs8qrXr064eHhJCUl8csvv9C9e3d27txpbrVK1JgxYxg+fLjx+dWrVyVQFEIIIcRTxewg8e7btNnZ2Rw5coQNGzYwcuRIsytgaWlJlSpVAGjYsCEHDhxg5syZvPnmm2RlZZGYmGjSmxgTE4OXlxcAXl5e7N+/36S83NnPefPcPSM6JiYGR0dHbGxsCqyTlZUVVlZWxufJyclmt+txp9PpSExMNOscZ2dn2dNbCCGEeEKYHSQOGTKkwPQ5c+Zw8ODBB66QTqcjMzOThg0bYmFhwdatW+ncuTMAERERREVFERwcDEBwcDBfffUVsbGxeHh4ALB582YcHR2NPX/BwcH89ddfJtfYvHmzsQxRsMTERKatO4K1nUOx8ssMUSGEEOLJYnaQWJi2bdsyZswYsya2jBkzhrZt21KhQgVSUlJYsWIFO3bsYOPGjTg5OdG7d2+GDx+Oq6srjo6ODBo0iODgYJo0aQJA69atCQwM5N1332XKlClER0fz2WefMWDAAGNPYL9+/Zg9ezajRo2iV69ebNu2jVWrVrF+/fqSavoTS2aICiGEEE+vEgsSf/nlF7N7kWJjY3nvvfe4fv06Tk5O1KlTh40bN/LSSy8BMH36dFQqFZ07dyYzM5PQ0FDmzp1rPF+tVrNu3Tr69+9PcHAwdnZ2dO/enYkTJxrzBAQEsH79eoYNG8bMmTPx9fVl4cKFsvyNEEIIIUQRzA4S69evbzJxRa/XEx0dTVxcnEkAVxyLFi0q8ri1tTVz5sxhzpw5hebx9/fPdzv5bi1atODIkSNm1U0I8XTI3aHFXDIGVwjxpDM7SOzQoYPJc5VKhbu7Oy1atKBGjRolVS8hhHgkzN2hJfccGYMrhHjSmR0kjh8//mHUQwghSo2MvxVCiPzkXokQQgghhMin2D2JKpWqyEW0ARRFIScn54ErJYQQQgghSlexg8Tffvut0GNhYWHMmjULnU5XIpUSQgghhBClq9hB4muvvZYvLSIigtGjR/Pnn3/SrVs3k6VnhBBCCCHE4+u+xiReu3aNPn36ULt2bXJycggPD2fp0qX4+/uXdP2EEEIIIUQpMCtITEpK4uOPP6ZKlSqcPHmSrVu38ueff1KrVq2HVT8hhBBCCFEKin27ecqUKUyePBkvLy/++9//Fnj7WTx8Op2OxMREs8+ThX+FEEIIYY5iB4mjR4/GxsaGKlWqsHTpUpYuXVpgvjVr1pRY5UR+iYmJTFt3BGs7h2KfIwv/CiGEEMJcxQ4S33vvvXsugSMejbK48O/9bG2WkJAAev1DqpEQQgghHkSxg8QlS5Y8xGqIx939bG2WEHMVGyc37B5ivYQQQghxf8zelk+Iwpjbw5mWkvTwKiOEEEKIByIzGYQQQgghRD7SkyiEEGa6nzG4ssKAEOJxI0GiEEKYydwxuLLCgBDicSRBohBC3IeyuMqAEEKUJLn3IYQQQggh8pEgUQghhBBC5CNBohBCCCGEyEeCRCGEEEIIkY9MXBFCiIfsfpbMAVk2RwhRuiRIFEKIh+x+tq2UZXOEEKVNgkQhhHgEZMkcIcTjRu5jCCGEEEKIfCRIFEIIIYQQ+UiQKIQQQggh8pEgUQghhBBC5CMTV4QQogySZXOEEKVNgkQhhCiDZNkcIURpK9WPm5MmTeKZZ57BwcEBDw8POnToQEREhEmejIwMBgwYgJubG/b29nTu3JmYmBiTPFFRUbRv3x5bW1s8PDwYOXIkOTk5Jnl27NhBgwYNsLKyokqVKixZsuRhN08IIR5I7rI5xX1Y2zmUdpWFEE+QUg0Sd+7cyYABA9i7dy+bN28mOzub1q1bk5qaaswzbNgw/vzzT1avXs3OnTu5du0anTp1Mh7XarW0b9+erKws9uzZw9KlS1myZAnjxo0z5omMjKR9+/a0bNmS8PBwhg4dyvvvv8/GjRsfaXuFEEIIIR4XpXq7ecOGDSbPlyxZgoeHB4cOHaJ58+YkJSWxaNEiVqxYQatWrQBYvHgxNWvWZO/evTRp0oRNmzZx6tQptmzZgqenJ/Xq1eOLL77g448/ZsKECVhaWjJ//nwCAgKYOnUqADVr1mT37t1Mnz6d0NDQR95uIYQQQoiyrkyNbk5KSgIwjqc5dOgQ2dnZhISEGPPUqFGDChUqEBYWBkBYWBi1a9fG09PTmCc0NJTk5GROnjxpzJO3jNw8uWUIIYQQQghTZWbiik6nY+jQoTRr1oxatWoBEB0djaWlJc7OziZ5PT09iY6ONubJGyDmHs89VlSe5ORk0tPTsbGxMTmWmZlJZmam8XlKSsqDN1AIIYQQ4jFSZnoSBwwYwIkTJ1i5cmVpV4VJkybh5ORkfAQGBpZ2lYQQQgghHqkyESQOHDiQdevWsX37dnx9fY3pXl5eZGVlkZiYaJI/JiYGLy8vY567ZzvnPr9XHkdHx3y9iABjxowhKSnJ+Dh16tQDt1EIIYQQ4nFSqkGiXq9n4MCB/Pbbb2zbto2AgACT4w0bNsTCwoKtW7ca0yIiIoiKiiI4OBiA4OBgjh8/TmxsrDHP5s2bcXR0NPYABgcHm5SRmye3jLtZWVnh6OhofDg4yLISQgghhHi6lOqYxAEDBrBixQr++OMPHBwcjGMInZycsLGxwcnJid69ezN8+HBcXV1xdHRk0KBBBAcH06RJEwBat25NYGAg7777LlOmTCE6OprPPvuMAQMGYGVlBUC/fv2YPXs2o0aNolevXmzbto1Vq1axfv36Umu7EEIIIURZVqpB4rx58wBo0aKFSfrixYvp0aMHANOnT0elUtG5c2cyMzMJDQ1l7ty5xrxqtZp169bRv39/goODsbOzo3v37kycONGYJyAggPXr1zNs2DBmzpyJr68vCxculOVvhBBPlPvZyk+28RNCFKZUg0S9Xn/PPNbW1syZM4c5c+YUmsff35+//vqryHJatGjBkSNHzK6jEEI8Lszdyk+28RPC1KRJk1izZg1nzpzBxsaGpk2bMnnyZKpXr27Mk5GRwYgRI1i5cqVJ51XuKirx8fF0796d7du3U7VqVX788Ufq169vPH/AgAFUqlSJESNGPPL2mUs+PgohxBPEnK38ZBs/IUyVxE5wX331FSkpKRw+fJgWLVrQp08f47G9e/eyb98+hg4d+iibdd/KzDqJQgghhBClqSR2gjt9+jRdu3alWrVq9O3blwULFgCQnZ1Nv379WLhwIWq1+pG37X5IkGiGnJwcsrOzAVCpVKjVarRaLTqdzpgnNz0nJ8fkdrparUalUhWanltuLo1GY7xmXoZz9Sh6rWm6oga9HgVdnlQFvaJCQW9Sd0VR0Gg0hdZdq9WSk5ODCh2KXoseBRQVil4H3Km7HhUoCopehxo9yu163Um/q463O65z65h7Drd/HqZ1z98mY37DD6LAtqLX3cljSDV8zVf3gttUeP6i2qRHdddrcndbTdqUL39u3QtvU96fr/F1LaJNBb8eRbfpnq9HYa8fFFF303SVMb/p61RYm+79ehSQfvs6xXo9Cnv9ivh7Qq8v8PUoqk2mr8e9/57AcA0LlR4bRQtK7s/g7rqbtsnJSkGvARtFW8Dvngr0pvlVFjqysrJIS0tDq73T/uL8H/Eo/98rLN3CwgKdTldg3QtLlzY9WW1Sq9VYW1uj0+kKbRMYNsVITk42HreysjJObi2KuTvBNWnShLp167Jt2zbef/99Nm7cSJ06dQCYMmUKLVq0oFGjRve8blkhQaIZwsLCsLW1BaBChQrUr1+fY8eOERUVZcxTvXp1atSowf79+4mLizOm16tXD39/f3bt2mWyg0twcDAeHh5s2rTJ5A+rZcuW2NjY5BtrGRwcjBU5BKT/a0zToeKibXVsdKl4Z142pmcpllyxqYyzkm6yBaG7uztNmzbl7NmzREREGNPvblOQBkiPIUFTjgRLdzwzr2Cru9PlHmfpRYrGhfIZkQS4ZAHpkJ7IdSs/0tX2+KefQ5XnDemydSVyFI2x7gEuAOlE4oFGn4NfxoUi2xTgAunaTK7jjYM2EfesaGP+NJUd0dYVcMm+iUvODWO6na2aS9nWuGVF46hNMqYX1ia9pSU39VA+IxJLfZYxvag2qYGG9omQnmhMj7SpVmibnDQ6auTJn/s6FdWmSi7pxp9vstqJG1Y+RbYpIE/+vK9TUW3KfT0u611NXqfC2hTgAlp9OpfwLvR37+42udirOJtpne91KqxNFtYarmuti/zdu7tNAPXsElHneT3u/t3L2yYblZ46eV6Pe/09OWgTTV6Pwn738rYp7+tRnL8nS30WdSo44OBgi16dhR4Fjd70jVqraPKnu7iQpVehVmWh1pu+UecoFijoTdL1LpbcvHmTuLg4srLu/BzVajVWVlZkZ2ebBAgajQZLS0uysrJM/r+ysLDAwsKCzMxMkzd8S0tLNBoNGRkZJm/sVlZWqNVq0tPTTd7Yra2tURSF9PR0k7rb2Nig1+vJyMgwpimKgo2NDVqt1mSHLJVKhbW1NTk5OdKmp6RNVlZWxt/jXLnvueHh4QD5NsUYP348EyZMoCj3uxPc6NGj6d+/P5UrV6ZixYosWrSIs2fPsnTpUsLCwujXrx+bNm2iUaNG/PDDDzg5ORVZj9Kk6Isze+Qpd+XKFfz8/IiMjKR8+fJA6X1SS05OZt6Oc9g7OJqkF9XzkZacQJ/nA3BxcTGkFuOT2s2bN1n4vwvYOjgVq+fj5rUoFAsrXN09it2TePPaZRQLK1zcvUzSC2uTMb+Hd7F7EuOuXUaxsKacu8dddS+4TYXnL7xNcdcuobnd9sLamrdNcVcv3pX/3j2J8Xl+vsXpSSz49Si6J/Ger0dhr1+Rr4dp+o1rl8HCGjd3j2L1JN779cjfprhrUWgsLIv3ehT2+t2jJzH+2qV8r0dRPYmmr8e9/578bLLwtdXhVs4daxs7UCnGHt685eeemUubkw2oUGs0JumG7MrtpDvpOp0WVztDIJD3/yVFUVAUBb1e/1DT8/7/k5sO+Sc1FpauUqkeeh2lTWW7TXq9nuvXr6NWqylfvryxDrnvrRcvXiQgIIBTp04Z37+heD2J/fv35++//2b37t3GjT5WrFhBz549TQJegGeffZaWLVsyefLkAstq1aoVQ4YM4dKlS6xbt47169fTp08f3NzcmDp1apH1KE3Sk2gGjUaDhYWFSZparS5wbEFukFfc9LvLLSzd8Aeg3L5teRdFQU/+dD2KWXVXq9WG2wCoTK6jVwqe56RXVGhRUN1VrwLrCMY65p5D7n8sBdQ9b5uM+YtoK4rK5K1Rj4Jyj7pjVv6C2qSgK+Q1KbCOheUvok0F/3zNfT2KblOxXg8KeP2KrLtpug7FEK7d9ToVVkdzX7+813l4r4dS4M+3qDaZ83qoFAVvWz2ubuWwsXdEU8j/DQVSVIYPgcU8R6vVYm1tVej/S0I8Dtzd3bl27RqKouR7n8v93XZwcMDR0bGg0wuUuxPcrl27Ct0JLm9vYt6d4O62ePFinJ2dee211+jUqRMdOnTAwsKCN954g3HjxpnR0kdPZjcLIUQZYqnSo1YUNJb3Hi8lhDDcLgdMbqHfr5LYCS6vuLg4Jk6cyHfffWesY+6dw+zs7BKp88MkHx+FEKJMuT1ZR1HukU8IASX7t1ISO8HlNXToUEaMGGG81d2sWTN++uknWrduzYIFC2jWrFmJ1f1hkJ5EIYQQQggMO8ElJSXRokULvL29jY+ff/7ZmGf69Om8/PLLdO7cmebNm+Pl5cWaNWvylbVx40bOnTvHhx9+aEwbOHAglSpVonHjxmRlZTF+/PhH0q77JT2JQgjxGNDpdCQlJhaZJzs76/bEtGKOSdRp0WQXPibxcduyL3eSwpEjR6hXr15pVweAM2fO0KNHD8LDw6lRo4Zxtm1pqlixIkOHDjUu6KwoCr/99hsdOnS47zJLooyyoKR2ggMIDQ3Nt/2vra0tq1ateqA6PkoSJAohxGMgKTGRBVuOF7lLilarQ1EodmCn0+mxsVAKzJ9+K4Wh7eoWuGWfWq0u8BZfjx49WLp0KZMmTWL06NHG9N9//52OHTsW6w34STN+/Hjs7OyIiIjA3t6+tKtToOvXrxtXv7iXCRMm8Pvvv+cLds0pQzw+JEgUQojHhLWdA7YOzoUe12q1t4PE4u3mYBg0r0dfQJCoy9ISdyuTHAvTpT70Wi2ezraF9j5aW1szefJkPvjggycmaMjKyjJOjjDX+fPnad++Pf7+/mWmTncrbFbuoy5DlD2Pz30EIYQQJU5RFFSKqoCHglqlNi6VlftQ7rGdWEhICF5eXkyaNKnQPBMmTMh3O3jGjBlUrFjR+LxHjx506NCBr7/+Gk9PT5ydnZk4cSI5OTmMHDkSV1dXfH19Wbx4cb7yz5w5Q9OmTbG2tqZWrVrs3LnT5PiJEydo27Yt9vb2eHp68u6773Ljxp2F0Fu0aMHAgQMZOnQo5cqVy3fLMJdOp2PixIn4+vpiZWVFvXr1TLZ1UxSFQ4cOMXHiRBRFKXTx5tzrDRw4ECcnJ8qVK8fYsWNNel4rVqzIF198wXvvvYejoyN9+/YFYPfu3Tz//PPY2Njg5+fH4MGDTfYZjo2N5ZVXXsHGxoaAgACWL1+e7/qKovD7778bn1+5coW33noLV1dX7OzsaNSoEfv27WPJkiV8/vnnHD161Lhu4ZIlSwos4/jx47Rq1QobGxvc3Nzo27cvt27dMh7PfX2//fZbvL29cXNzY8CAASZrBs+dO5eqVatibW2Np6cnr7/+eoE/P/HwSJAohBCixKjVar7++mu+++47rly58kBlbdu2jWvXrrFr1y6mTZvG+PHjefnll3FxcWHfvn3069ePDz74IN91Ro4cyYgRIzhy5AjBwcG88sor3Lx5E4DExERatWpF/fr1OXjwIBs2bCAmJoYuXbqYlLF06VIsLS35559/mD9/foH1mzlzJlOnTuXbb7/l2LFjhIaG8uqrr3L27FnAcAs2KCiIESNGcP36dT766KNC27p06VI0Gg379+9n5syZTJs2jYULF5rk+fbbb6lbty5Hjhxh7NixnD9/njZt2tC5c2eOHTvGzz//zO7duxk4cKDxnB49enD58mW2b9/OL7/8wty5c4mNjS20Hrdu3eKFF17g6tWrrF27lqNHjzJq1Ch0Oh1vvvkmI0aMICgoiOvXr3P9+nXefPPNfGWkpqYSGhqKi4sLBw4cYPXq1WzZssWkXgDbt2/n/PnzbN++naVLl7JkyRJj0Hnw4EEGDx7MxIkTiYiIYMOGDTRv3rzQeouHQ243CyGEKFEdO3akXr16jB8/nkWLFt13Oa6ursyaNQuVSkX16tWZMmUKaWlpfPLJJwCMGTOGb775ht27d9O1a1fjeQMHDqRz586AYbbqhg0bWLRoEaNGjWL27NnUr1+fr7/+2pj/xx9/xM/Pj3///Zdq1aoBULVqVaZMmVJk/b799ls+/vhj47UnT57M9u3bmTFjBnPmzMHLywuNRoO9vf09b8f6+fkxffp0FEWhevXqHD9+nOnTp9OnTx9jnlatWjFixAjj8/fff59u3boZJ6BUrVqVWbNm8cILLzBv3jyioqL4+++/2b9/P8888wwAixYtombNmoXWY8WKFcTFxXHgwAHjeNQqVaoYj9vb26PRaIpsz4oVK8jIyGDZsmXY2dkBMHv2bF555RUmT56Mp6cnAC4uLsyePRu1Wk2NGjVo3749W7dupU+fPkRFRWFnZ8fLL7+Mg4MD/v7+1K9fv8ifoSh50pMohBCixE2ePJmlS5dy+vTp+y4jKCjIZFKNp6cntWvXNj5Xq9W4ubnl6xnLu6ixRqOhUaNGxnocPXqU7du3Y29vb3zUqFEDMIwfzNWwYcMi65acnMy1a9fyrXPXrFmz+2pzkyZNTCYDBQcHc/bsWZPFlhs1amRyztGjR1myZIlJW0JDQ9HpdERGRnL69Gk0Go1JW2rUqJFv3+G8wsPDqV+/foETlorr9OnT1K1b1xggguHnotPpiIiIMKYFBQWZ7Prl7e1tfC1feukl/P39qVSpEu+++y7Lly8nLS3tvusk7o8EiUIIIUpc8+bNCQ0NZcyYMfmO5e7lm9fd+9dDwduSFpR2997CRbl16xavvPIK4eHhJo+zZ8+a3M7MG+CUFXfX6datW3zwwQcm7Th69Chnz56lcuXK93UNGxubkqhqsRT1Wjo4OHD48GH++9//4u3tzbhx46hbty6J91gGSpQsCRKFEEI8FN988w1//vknYWFhJunu7u5ER0ebBIoluX7g3r17jd/n5ORw6NAh4y3WBg0acPLkSSpWrEiVKlVMHuYEho6Ojvj4+PDPP/+YpP/zzz8EBgaaXed9+/bla0PVqlVNetru1qBBA06dOpWvHVWqVMHS0pIaNWoY258rIiKiyECrTp06hIeHEx8fX+BxS0vLe24lV7NmTY4ePWoygeaff/4xDhsoLo1GQ0hICFOmTOHYsWNcvHiRbdu2Fft88eAkSBRCiMdERmoKaSmJRTySbj+KylO8/BmpKQ9c39q1a9OtWzdmzZplkt6iRQvi4uKYMmUK58+fZ86cOfz9998PfL1cc+bM4bfffuPMmTMMGDCAhIQEevXqBRi2XYuPj+ett97iwIEDnD9/no0bN9KzZ0+z99EdOXIkkydP5ueffyYiIoLRo0cTHh7OkCFDzK5zVFQUw4cPJyIigv/+979899139yzn448/Zs+ePQwcONDYG/rHH38YJ4hUr16dNm3a8MEHH7Bv3z4OHTrE+++/X2Rv4VtvvYWXlxcdOnTgn3/+4cKFC/z666/GQL9ixYpERkYSHh7OjRs3yMzMzFdGt27dsLa2pnv37pw4cYLt27czaNAg3n33XeN4xHtZt24ds2bNIjw8nEuXLrFs2TJ0Op1ZQaZ4cDJxRQghHgNOzs70DaldZB5zd1y5V36nIsauFdfEiRNNtjQDQ0/T3Llz+frrr/niiy/o3LkzH330EQsWLHjg64GhB/Obb74hPDycKlWqsHbtWsqVKwdg7P37+OOPad26NZmZmfj7+9OmTRuzd5cZPHgwSUlJjBgxgtjYWAIDA1m7di1Vq1Y1u87vvfce6enpPPvss6jVaoYMGWJc5qYwderUYefOnXz66ac8//zz6PV6KleubDLjePHixbz//vu88MILeHp68uWXXzJ27NhCy7S0tGTTpk2MGDGCdu3akZOTQ2BgoHF3kc6dO7NmzRpatmxJYmIiixcvpkePHiZl2NrasnHjRoYMGcIzzzyDra0tnTt3Ztq0acX+eTg7O7NmzRomTJhARkYGVatW5b///S9BQUHFLkM8OEX/NC6Bb6YrV67g5+fH5cuX8fX1LdW6xMfHM3f7OewcnYt9TmpyIh+2rGLWQGRzrxN39RIqCyvcPIq/oKq558g15BpPwzVsVFrqu2Tj6e2DhaUVGoviBXwA2Vm3g75inmNufjAswO3hUPhWfsJ8LVq0oF69esyYMaO0q/JYysjIIDIykoCAAKytrU2OlaX378eR/JU/BXQ6HQkJCWadk5CQAPL5QQghhHhqSZD4FMhITWHe1ps4u7kX+5yEmKvYOLlR9ub3CSGEEOJRkCDxKWFt52DWLeq0lKSHVxkhhBBGO3bsKO0qCFEgmd0shBBCCCHykSBRCCGEEELkI0GiEEIIIYTIR8YkCiGEKD69npycHLNOUavVJvsSCyEeDxIkCiGEKDadTkdcSgbqYi7Yrddq8XS2lXUVhXgMyV+tEEIIs6hU6iL3FM7LvI3uhBBliYxJFEII8VRQFIXff/+9tKvxwCZMmEC9evVKuxriKVCqQeKuXbt45ZVX8PHxKfCPV6/XM27cOLy9vbGxsSEkJISzZ8+a5ImPj6dbt244Ojri7OxM7969uXXrlkmeY8eO8fzzz2NtbY2fnx9Tpkx52E0TQoin1sH9e/FxsaPbGx3NPrdixYqP3fZ0LVq0YOjQoQ+l7ILeGz/66CO2bt36UK4nRF6lGiSmpqZSt25d48bhd5syZQqzZs1i/vz57Nu3Dzs7O0JDQ8nIyDDm6datGydPnmTz5s2sW7eOXbt2mWyKnpycTOvWrfH39+fQoUP83//9HxMmTCixjeSFEEKYWrFsKb0/6M/ePbuJvn69tKtz37Kyskq7CgWyt7fHzc2ttKshngKlGiS2bduWL7/8ko4d83/a1Ov1zJgxg88++4zXXnuNOnXqsGzZMq5du2b8VHX69Gk2bNjAwoULady4Mc899xzfffcdK1eu5Nq1awAsX76crKwsfvzxR4KCgujatSuDBw9m2rRpj7KpQghx3/R6PelZ2lJ56M3cwz311i3++O0XuvfuS0jrNqz673/y5fnzzz955plnsLa2ply5csb3gBYtWnDp0iWGDRuGoijGGdEF3V6dMWMGFStWND4/cOAAL730EuXKlcPJyYkXXniBw4cPm1X3Fi1aMHDgQIYOHUq5cuUIDQ0F4MSJE7Rt2xZ7e3s8PT159913uXHjBgA9evRg586dzJw501jnixcv3vO83OsNHjyYUaNG4erqipeXFxMmTDAez21fx44dURTl/9u787Co6v2B4+8zLMMm4AYjhmiJhhtqJqGpWJhomVrXcruKmt4sM69i6s9cSLPccl+ym2ilZZkauSNJKhEuqbmFS5hLgqQgILLO+f1BTAwDMqMooJ/X88zjc875fLcz33E+nG0My0X3h16v57333uORRx5Bq9XSvHlztm/fbth+/vx5FEVhw4YNdOzYEQcHB3x9fYmJibFo/4iHT4W9cSU+Pp6EhAQCAwMN61xcXPDz8yMmJobevXsTExODq6srrVq1MsQEBgai0WiIjY2lZ8+exMTE0L59e2xtbQ0xnTt3ZubMmSQnJ1O1alWTtrOyssjKyjIsp6Wl3aNRCiFE6TJz9ATMiSqXtqNCArC3Ne8mFYDvNn5Lfe8G1PduwMuv9mHy+LFMmzzRsH3Lli307NmTiRMn8tlnn5Gdnc3WrVsB2LBhA76+vgwbNoyhQ4da1M+0tDQGDhzIokWLUFWVuXPn0rVrV86cOUOVKlXMrmf16tUMHz6c6OhoAFJSUnjmmWd47bXXmDdvHrdu3WLcuHG88sor/PDDDyxYsIDTp0/TpEkT3nvvPQBq1qxZarnC7Y0ePZrY2FhiYmIIDg6mbdu2dOrUiQMHDuDm5kZYWBhBQUEl3iy0YMEC5s6dy8cff0yLFi1YuXIlL774IidOnMDb29sQN3HiRObMmYO3tzcTJ06kT58+nD17Vu48FyWqsDMjISEBAHd3d6P17u7uhm0JCQm4ubkZbbe2tqZatWpGMfXq1TOpo2BbcUniBx98QGhoaNkMRAghHiJffr6Kf73aB4BnAp9jVOowdu/ezTPPPAPA9OnTeeWVV5g0aZKhTOPGjcnNzcXZ2RkrKyscHBxwd3e36NmKBfUXWLFiBa6urvz444+88MILZtfj7e1tdN369OnTadGiBTNmzDCsW7lyJZ6enpw+fZoGDRpga2uLg4MDOp3OELN48eJSywE0a9aMKVOmGNpevHgxkZGRdOrUiZo1awLg6upqVHdRc+bMYdy4cfTu3RuAmTNnsnv3bubPn290OVdISAjPP/88AKGhoTRu3JizZ8/y+OOPm71/xMOlwiaJ5WnChAmMHj3asHz58mUaNWpUjj0SQjzM7Gw0RIUElBqXk52NoihY25j3DENz4u1szL8q6eyZ0xw+dJCVa9YB+X+0d+v+Ess/+ZQmT7YF4MjRo7zSbyBX07KKrSNPr5J+K4e8vDyLjnAlJiby7rvvEhUVxdWrV8nLyyMjI4MLFy6YXQfAE088YbR89OhRdu/ejZOTk0nsuXPnDMleUeaWa9asmdG2WrVqcfXqVbP7m5qayp9//knbtm2N1rdt25ajR48arSvcVq1atQC4evWqJImiRBU2SSz4qykxMdEwmQuWC67F0Ol0Jh+m3Nxcrl+/biiv0+lITEw0iilYLukvM61Wi1arNSynpqbe3WCEEOIuKIpi1ilfa6z+TvrMOz1saXxp1n62itzcXJo3fNSwTlVVbLVabqan4+zigr2dPYpGU/JzFhVAY5yYajQak2sjc3JyjJYHDhzItWvXWLBgAV5eXmi1Wvz9/S2++cTR0dFoOT09nW7dujFz5kyT2MLfTUWZW86mSIKuKAp6vd6iPpurcFsFR2nvVVviwVBhn5NYr149dDqd0W3+qampxMbG4u/vD4C/vz8pKSkcOnTIEPPDDz+g1+vx8/MzxOzZs8foP5SIiAgaNmxY7KlmIYQQlsvNzeWbr9Yy9f0P2bUv1vDaERWNu07HxvVfA+DTpAn7ftxdYj22Nrbk5Rk/grtmzZokJCQYJYpHjhwxiomOjmbkyJF07dqVxo0bo9VqjW4SuVMtW7bkxIkT1K1bl/r16xu9ChJKW1vTPptTzhw2NjYmdRfm7OyMh4eH4RrKAtHR0XIGTNy1ck0S09PTOXLkiOHDHh8fz5EjR7hw4QKKojBq1CimT59OeHg4x44dY8CAAXh4eNCjRw8AfHx8CAoKYujQoezfv5/o6GhGjBhB79698fDwAKBv377Y2toyZMgQTpw4wbp161iwYIHR6WQhhBB3J2L7Vm6kJNP338H4NGpseD3u04iuL3Rn7eerABgzbiIb13/NrBnTOB33G6dOHGfRvDmGejzreBEbE83ly5cNSV5AQABJSUnMmjWLc+fOsWTJErZt22bUvre3N59//jmnTp0iNjaWfv36YW9vf9fjevPNN7l+/Tp9+vThwIEDnDt3jh07djBo0CBD8la3bl1iY2M5f/48f/31F3q93qxy5qhbty6RkZEkJCSQnJxcbMzYsWOZOXMm69atIy4ujvHjx3PkyBHefvvtux6/eLiVa5J48OBBWrRoQYsWLQAYPXo0LVq0YPLkyQC88847vPXWWwwbNownn3yS9PR0tm/fjp2dnaGONWvW8Pjjj/Pss8/StWtXnn76aaNnILq4uLBz507i4+N54oknGDNmDJMnTzZ6lqIQQoi7s/bz1bQLeAZnFxeTbV27vcjRw79w8vgx2rZrzyer17Bz6xYCn/bj5W5dOHLooCH2nYmTuHjhDxo2bGi4ccPHx4elS5eyZMkSfH192b9/PyEhIUZtfPrppyQnJ9OyZUv+/e9/M3LkSJMbG+9EwVG6vLw8nnvuOZo2bcqoUaNwdXVF8/dp8ZCQEKysrGjUqBE1a9bkwoULZpUzx9y5c4mIiMDT09PwXVnUyJEjGT16NGPGjKFp06Zs376d8PBwozubhbgTimrpQ7AeQpcuXcLT05OLFy/yyCOPlGtfrl+/ztLdZ3F0djW7TNLlP9DYaKnuVvLdcXdbRtqQNqSNsom31+TRomoO7rU8sLHVmn0TCtybG1fKo428vDzcqmjl0SzCLJmZmcTHx1OvXj2jg0hQsb6/K6MKe02iEEIIIYQoP5IkCiGEEEIIE5IkCiGEEEIIE5IkCiGEEEIIE5IkCiGEEEIIE3LrmBBCiIpFVcnNzbWoiJWVlUW/9SyEKJ0kiUIIISoUvV5PUlomVtbmPTZHzcvD3dVBHpkjRBmTT5QQQogKR6OxKvn3nYsw//dLhBCWkGsShRBCCCGECUkShRBCVDojhw8luG8vw/Kzzz7LqFGj7ns/oqKiUBSFlJSU+952WQsICCiXfSgqLkkShRBClImRw4eic7FH52KPZw1nnmremPlzZlp8E8qd+Oabb5g2bZpZsZUlsVMUhU2bNpV5vSWNf8OGDWbvQ/FwkGsShRBClJmOgc+xYOnHZGVlEblzBxNCRmFjY8OoseNNYrOzs7G1tS2TdqtVq1ZpblzJycnBxoLfsr5fqlWrVt5dEBWMHEkUQoiKTlUh52apLyUnAyUnw6xYs+NV1aKuarW2uLnr8KzjRfBrw3i6QwA7t28F/jlFPH/2THwb1qPtE80AuHzpIkMH9qNBHR2Pe3kw+N99uHjhD0OdeXl5TPm/d2hQR4dP3dq8N+n/UIv0q+jp5qysLMaNG4enpydarZb69evz6aefcv78eTp27AhA1apVURSF4OBgIP+u6g8++IB69ephb2+Pr68v69evN2pn69atNGjQAHt7ezp27Mj58+dL3SeKorBs2TJefPFFHB0def/99wH47rvvaNmyJXZ2djz66KOEhoYajrrWrVsXgJ49e6IoimG5tHIF7f3vf/+jZ8+eODg44O3tTXh4OMBtx1/0dHNycjIDBgygatWqODg40KVLF86cOWPYvmrVKlxdXdmxYwc+Pj44OTkRFBTElStXSt0nonKoHH92CSHEwyw3A/dFj5ZL04lv/Q42jndc3s7OnpTryYblvT9G4VTFmXWbtgD5R9V6v/QirZ7047ttu7CytuajmTPo/8pL7I45iK2tLcsWzWfdmi+Yt3g53g0fZ/miBWzbHM7T7TuU2O6AAQOIiYlh4cKF+Pr6Eh8fz19//YWnpyfffvstL7/8MnFxcTg7O2Nvbw/ABx98wBdffMHy5cvx9vZmz5499O/fn5o1a9KhQwcuXrzISy+9xJtvvsmwYcM4ePAgY8aMMWs/TJ06lQ8//JD58+djbW3N3r17GTBgAAsXLqRdu3acO3eOYcOGATBlyhQOHDiAm5sbYWFhBAUFGe70Lq1cgdDQUGbNmsXs2bNZtGgR/fr1448//rjt+IsKDg7mzJkzhIeH4+zszLhx4+jatSsnT540HAnNyMhgzpw5fP7552g0Gvr3709ISAhr1qwxa7+Iik2SRCGEEGVOVVX2Ru1mz+5Igl/7j2G9g4MjHy1aZjjNvH7dl6h6PR8tXmZ4GPbchUtpXL8OP+3dQ8CzgXyybDFvjQ7h+Rd7ADBr/iKifogose3Tp0/z9ddfExERQWBgIACPPvpPkl1wWtXNzQ1XV1cg/8jjjBkz2LVrF/7+/oYy+/bt4+OPP6ZDhw4sW7aMxx57jLlz5wLQsGFDjh07xsyZM0vdH3379mXQoEGG5cGDBzN+/HgGDhxoaGvatGm88847TJkyhZo1awLg6uqKTqczlAsNDb1tuQLBwcH06dMHgBkzZrBw4UL2799PUFBQseMvqiA5jI6Opk2bNgCsWbMGT09PNm3aRK9e+TcN5eTksHz5ch577DEARowYwXvvvVfq/hCVgySJQghR0Vk75B/RK0Vudg6KomBlY95/7WbFWzuY20sAIrZv41GPGuTm5KDX6+nxUi/GvDPBsN2nUWOj6xBPHPuV+N/P8Vjtmv9UokJWZibn438n9cYNEhMSaNmq9T9dsrbGt0XLf045qyqqqqLX68nNzeXQoUNYWVnRtm3bYm+aycvL+7vYP6esz549S0ZGBp06dTKKzc7OpkWLFgCcOnUKPz8/o+0FCWVpWrVqZbR89OhRoqOjDaeeC/qVmZlJRkYGDg7F73dzyzVr1syw3dHREWdnZ65evWpWXyF/rNbW1kbjrV69Og0bNuTUqVOGdQ4ODoYEEaBWrVoWtSMqNkkShRCiolMUs075qmr237Fm/lKJhfHmaNuuAzM/WoiNrQ26Wh6oer3Rz+U5OBonPzdv3qRZ8xYs/WSVYV1OTjaKouCuq2VWm3q9npw8PRnZeVxNyyLr76+2q2lZ2NjoTeKTM7KBf5JFgPT0dAC2bNlC7dq1jeK1Wq1Z/bgdR0fj9y89PZ3Q0FBeeuklk1g7O7sS6zG3XNEbYxRFQa833Rd3q7h2il4vKiovSRKFEEKUGQdHB+oVOrKUk5192/hmvs0J37CeGjVrUsXZ2VBGURSs/05A3HU6fjm4H/+2TwOQm5vLr0cO09S3eaGaFDQaBSsrKxo3aYZer2d/zE+07/iMSZsFyVThJLFRo0ZotVouXLhAhw7FX+vo4+NjuAGkwM8//3zb8ZWkZcuWxMXFUb9+/RJjbGxsjPpobrnSFBzJLVp3YT4+PuTm5hIbG2s43Xzt2jXi4uJo1KjRHbctKhe5u1kIIUS5eemV3lSrXp2BfXvx80/7+OP8eWKi9zJpwlj+vHwJgNdef5PF8+aybXM4Z07HMX7029y4caPEOut4efFK3/78d8R/2LY5nD/Onyd67x6+25B/p/IjnnVQFIUtW7aQlJREeno6VapUISQkhP/+97+sXr2ac+fO8csvv7Bo0SJWr14NwOuvv86ZM2cYO3YscXFxrF27llWrVt3RuCdPnsxnn31GaGgoJ06c4NSpU3z11Ve8++67hpi6desSGRlJQkICycnJZpcrjZeXF4qisHnzZsP4i/L29qZ79+4MHTqUffv2cfToUfr370/t2rXp3r37HY1ZVD6SJAohhCg3Dg4ObNoWQe1HPBncvw/tWzcnZNQIsjKzqFIl/8ji8LdG8a/efRg5fCgvBAbgWMWJLi+8eNt6Z360kBe692T8mLdp96QvISPfICMjA4BaHrUZM34iEydOxN3dnREjRgAwbdo0Jk2axAcffICPjw9BQUFs2bKFevXqAVCnTh2+/fZbNm3ahK+vL8uXL2fGjBl3NO7OnTuzefNmdu7cyZNPPslTTz3FvHnz8PLyMsTMnTuXiIgIPD09DddFmlOuNLVr1zbcAFN4/EWFhYXxxBNP8MILL+Dv74+qqmzdurVCPuNR3BuKKhcPlOrSpUt4enpy8eJFHnnkkXLty/Xr11m6+yyOzq5ml0m6/AcaGy3V3XSlB99hGWlD2pA2yibeXpNHi6o5uNfywMZWazjlao6ip2nLOv5BaiMvLw+3KtpK8wBuUbLMzEzi4+OpV6+eyfWcFen7uzKSI4lCCCGEEMKE/AklhBDi4aOqFv+mtJWVldGd2kI86CRJLGd6vd6iH5lPTk62+GeyhBBCGNPr9SSlZWJlbebjgvLycHd1kNPT4qEis72cpaSk8NHmw9g5VjErPjnxMvYu1bnzH8kSQggBoNFYGX7urjQlPyxGiAeXJIkVgJ1jFbNvRMlIK/mxD0KIB0H+6Uy5p7CCuYPT0yCnqO8H+azcO5IkCiFEBZKtV8hTVXKzs7DVlvzLG+L+svT0NMgp6vsl++8Htpt7VFiYT2auEEJUIHko/JmhwYq/UBQFOwfH/J/OM0NuTg4KCqpq3s+vWRovbSgWHRXU//2bypIk3jt6vZ6kpCQcHCQZvxdkjwohRAVzMdOWjNSr1MvVY2tj/n/TeXm5KIqCRmPmdXYWxksblrWh1+tJsdVYdIRLUSxLRAVoNBrq1Kkj++0ekCRRCCEqHIXfkjL5PVVF5+YGmHfNVfLVJBRrW1yr1bgn8dKGpW38SXZ2Ds5Vq5kVn5Vxk+AAH1xdXc1uQ+T/FrVGI499vhckSRRCiAoqVw+39OZ/+aVl6dHoVbR6845cWRovbdxBGzYOYO9qVnx2lp6bN29ia2trdhsArq6ukiSJe+KhShKXLFnC7NmzSUhIwNfXl0WLFtG6devy7pYQQghB5s00lkVew7V6TYvKjH6hBdWqmXe0UpjndvnC6NGjWbVqFY6Ojnz44Yf069fPUO6bb77hs88+4/vvvy+vrpephyZJXLduHaNHj2b58uX4+fkxf/58OnfuTFxcHG5ubuXdPSGEEMKiR6JB/nWPycnJFrUhRx5v73b5QmxsLGvXrmXnzp2cOXOGwYMH07lzZ2rUqMGNGzeYOHEiu3btKu8hlJmHJkn86KOPGDp0KIMGDQJg+fLlbNmyhZUrVzJ+/Phy7p0QQghhOUuPPt7JkUdLfxkMKnciert8QaPREBAQQKtWrWjVqhWjRo0iPj6eGjVq8M477zB8+HDq1KlTziMoOw9Fkpidnc2hQ4eYMGGCYZ1GoyEwMJCYmBiT+KysLLKysgzLN27kP8D60qVLhoepKoqClZUVeXl5Rg/y1Gg0aDSaEtcXfRhramoqVy/+jr2Dg9H6gocyFP2IJScloljbknMzpUi8Aqgm8XoUUpMS0NgYl9HnP/yBwveCqYD69/rUv/5pp2C9psjF84XX3ygUn9930/iiYyook/V3v4rre+Ex/RN/w6TvJY3pxl+JqFa2ZN9MKXasRfuYkpQIxe7fksd0IykRK5P9azzWwn009/0ovL6496Ok96/o+1HSWIuOqfT3w3hMhd+Pkuaepe9H0fiS3o/bjcmy96Ok+JI/T0Xfj5LGejefp4J99c/7UfrnqaCMapVfprTPU+H4ou/H7caUkpRoMn9vN6aUEt+PkseUZrJ/TcdaeEym8bf/PCn8s3+zb6aU+nmimPjSPk8FZUp+P0zHVNr7V9yYkpMS0VjbYlXoN2Fu939EZkYGx48fx9nZ2bA+/67t/O+twjQaDYqikJyczNro02jt8r+n8v4eolWRzhSsz83KoG/bBoY2rKysUFUVvd74cUNWVlbo9XrDd6Wrq6vhu1Wv1xvF3+l37qVLl/L37Y0bRmPWarVotVqKKi1feOONN1ixYgXJycn8/vvv3Lp1i/r167Nv3z5++eUXli5dalJnpaY+BC5fvqwC6k8//WS0fuzYsWrr1q1N4qdMmZL/GZOXvOQlL3nJS14P3GvKlCl3nC9MmTJFfeyxx9QmTZqoGzZsULOystQmTZqoBw8eVBctWqQ2aNBAbdOmjXr8+PGySWLK0UNxJNFSEyZMYPTo0Ybl3NxcTp06haenJ8888wxRUVEllg0ICCh2e1paGo0aNeLkyZNUqWLe7zRXNCWNrTK0dbf1WVreknhzYkuLkXlXMduTeSfzrrzau5v6Kuu8A9O5p9fruXDhAo0aNTJ62HZxRxHNNXXqVKZOnWpYDg0NJTAwEBsbG6ZPn86xY8fYvHkzAwYM4NChQ3fcTkXwUCSJNWrUwMrKisTERKP1iYmJ6HQ6k/jiDkO3bdsWyH8e0yOPPFJiWyVtT01NBaB27dpGh7wrk9LGXpHbutv6LC1vSbw5sTLv7s+8K+v2ZN7JvCuv9u6mvso676D4uWfJNYKW5gu//fYbX3zxBYcPH2blypW0b9+emjVr8sorrzB48GDS0tIq7R9KYHqJxwPJ1taWJ554gsjISMM6vV5PZGQk/v7+FtX15ptv3tX2yux+jq2s27rb+iwtb0m8ObEy7ypnezLvKq/KPO/utr6Hed5Zki+oqsp//vMfPvroI5ycnMjLyyMnJwfA8G/R6zwrG0VVC13p+QBbt24dAwcO5OOPP6Z169bMnz+fr7/+mt9++w13d/d73n5qaiouLi4mF88KcS/JvBPlQeadKC9lMffMzRc++eQTduzYwfr16wHYv38/nTp1YseOHWzbto3169dz4sSJMhlXeXkoTjcDvPrqqyQlJTF58mQSEhJo3rw527dvvy8JIuSfwp4yZcpdXQchhKVk3onyIPNOlJeymHvm5AuJiYm8//77/PTTT4Z1rVu3ZsyYMTz//PO4ubmxevXquxpLRfDQHEkUQgghhBDmeyiuSRRCCCGEEJaRJFEIIYQQQpiQJFEIIYQQQpiQJFEIIYQQQpiQJPEe27NnD926dcPDwwNFUdi0aVN5d0k8gEqbZ6qqMnnyZGrVqoW9vT2BgYGcOXOmfDorKq2ymGfXr1+nX79+ODs74+rqypAhQ0hPT7+PoxAV3f2aZ7/++ivt2rXDzs4OT09PZs2ada+HVulIkniP3bx5E19fX5YsWVLeXREPsNLm2axZs1i4cCHLly8nNjYWR0dHOnfuTGZm5n3uqajMymKe9evXjxMnThAREcHmzZvZs2cPw4YNu19DEJXA/ZhnqampPPfcc3h5eXHo0CFmz57N1KlTWbFixT0fX6VSfj8b/fAB1I0bN5Z3N8QDrug80+v1qk6nU2fPnm1Yl5KSomq1WvXLL78shx6KB8GdzLOTJ0+qgHrgwAFDzLZt21RFUdTLly/ft76LyuNezbOlS5eqVatWVbOysgwx48aNUxs2bHiPR1S5yJFEIR5w8fHxJCQkEBgYaFjn4uKCn58fMTEx5dgz8SAxZ57FxMTg6upKq1atDDGBgYFoNBpiY2Pve59F5VNW8ywmJob27dtja2triOncuTNxcXEkJyffp9FUfJIkCvGAS0hIADD5dSF3d3fDNiHuljnzLCEhATc3N6Pt1tbWVKtWTeaiMEtZzbOEhIRi6yjchpAkUQghhBBCFEOSRCEecDqdDsj/rdHCEhMTDduEuFvmzDOdTsfVq1eNtufm5nL9+nWZi8IsZTXPdDpdsXUUbkNIkijEA69evXrodDoiIyMN61JTU4mNjcXf378ceyYeJObMM39/f1JSUjh06JAh5ocffkCv1+Pn53ff+ywqn7KaZ/7+/uzZs4ecnBxDTEREBA0bNqRq1ar3aTQVn3V5d+BBl56eztmzZw3L8fHxHDlyhGrVqlGnTp1y7Jl4kJQ2z0aNGsX06dPx9vamXr16TJo0CQ8PD3r06FF+nRaVzt3OMx8fH4KCghg6dCjLly8nJyeHESNG0Lt3bzw8PMppVKKiuR/zrG/fvoSGhjJkyBDGjRvH8ePHWbBgAfPmzSuPIVdc5X179YNu9+7dKmDyGjhwYHl3TTxASptner1enTRpkuru7q5qtVr12WefVePi4sq306LSKYt5du3aNbVPnz6qk5OT6uzsrA4aNEhNS0srh9GIiup+zbOjR4+qTz/9tKrVatXatWurH3744f0aYqWhqKqq3t+0VAghhBBCVHRyTaIQQgghhDAhSaIQQgghhDAhSaIQQgghhDAhSaIQQgghhDAhSaIQQgghhDAhSaIQQgghhDAhSaIQQgghhDAhSaIQosKpW7cu8+fPv22Moihs2rQJgPPnz6MoCkeOHAEgKioKRVFISUm5J/2bNGkSw4YNu21MQEAAo0aNuiftF+epp57i22+/vW/tCSEefJIkCiHuSFJSEsOHD6dOnTpotVp0Oh2dO3cmOjraEFM4kStrV65coUuXLsVua9OmDVeuXMHFxQWAVatW4erqWibtJiQksGDBAiZOnFgm9ZWVd999l/Hjx6PX68u7K0KIB4QkiUKIO/Lyyy9z+PBhVq9ezenTpwkPDycgIIBr167dl/Z1Oh1arbbYbba2tuh0OhRFKfN2//e//9GmTRu8vLzKvO670aVLF9LS0ti2bVt5d0UI8YCQJFEIYbGUlBT27t3LzJkz6dixI15eXrRu3ZoJEybw4osvAvmnjAF69uyJoiiG5XPnztG9e3fc3d1xcnLiySefZNeuXSZtpKWl0adPHxwdHalduzZLliwx2n67o5SFTzdHRUUxaNAgbty4gaIoKIrC1KlTee+992jSpIlJ2ebNmzNp0qQSx/7VV1/RrVs3o3U3b95kwIABODk5UatWLebOnWtS7vPPP6dVq1ZUqVIFnU5H3759uXr1KgCqqlK/fn3mzJljVObIkSMoisLZs2dRVZWpU6cajtx6eHgwcuRIQ6yVlRVdu3blq6++KrHvQghhCUkShRAWc3JywsnJiU2bNpGVlVVszIEDBwAICwvjypUrhuX09HS6du1KZGQkhw8fJigoiG7dunHhwgWj8rNnz8bX15fDhw8zfvx43n77bSIiIizua5s2bZg/fz7Ozs5cuXKFK1euEBISwuDBgzl16pShXwCHDx/m119/ZdCgQcXWdf36dU6ePEmrVq2M1o8dO5Yff/yR7777jp07dxIVFcUvv/xiFJOTk8O0adM4evQomzZt4vz58wQHBwP5Ce/gwYMJCwszKhMWFkb79u2pX78+3377LfPmzePjjz/mzJkzbNq0iaZNmxrFt27dmr1791q8j4QQoliqEELcgfXr16tVq1ZV7ezs1DZt2qgTJkxQjx49ahQDqBs3biy1rsaNG6uLFi0yLHt5ealBQUFGMa+++qrapUuXYuuOj49XAfXw4cOqqqrq7t27VUBNTk5WVVVVw8LCVBcXF5N2u3Tpog4fPtyw/NZbb6kBAQEl9vPw4cMqoF64cMGwLi0tTbW1tVW//vprw7pr166p9vb26ttvv11iXQcOHFABNS0tTVVVVb18+bJqZWWlxsbGqqqqqtnZ2WqNGjXUVatWqaqqqnPnzlUbNGigZmdnl1jnd999p2o0GjUvL6/EGCGEMJccSRRC3JGXX36ZP//8k/DwcIKCgoiKiqJly5asWrXqtuXS09MJCQnBx8cHV1dXnJycOHXqlMmRRH9/f5PlU6dOlekYhg4dypdffklmZibZ2dmsXbuWwYMHlxh/69YtAOzs7Azrzp07R3Z2Nn5+foZ11apVo2HDhkZlDx06RLdu3ahTpw5VqlShQ4cOAIZxe3h48Pzzz7Ny5UoAvv/+e7KysujVqxcAvXr14tatWzz66KMMHTqUjRs3kpuba9SGvb09er2+xKO7QghhCUkShRB3zM7Ojk6dOjFp0iR++ukngoODmTJlym3LhISEsHHjRmbMmMHevXs5cuQITZs2JTs7+z71+h/dunVDq9WyceNGvv/+e3JycvjXv/5VYnyNGjUASE5Otqidmzdv0rlzZ5ydnVmzZg0HDhxg48aNAEbjfu211/jqq6+4desWYWFhvPrqqzg4OADg6elJXFwcS5cuxd7enjfeeIP27duTk5NjKH/9+nUcHR2xt7e3qH9CCFEcSRKFEGWmUaNG3Lx507BsY2NDXl6eUUx0dDTBwcH07NmTpk2botPpOH/+vEldP//8s8myj4/PHfXL1tbWpB8A1tbWDBw4kLCwMMLCwujdu/dtE6zHHnsMZ2dnTp48abTOxsaG2NhYw7rk5GROnz5tWP7tt9+4du0aH374Ie3atePxxx833LRSWNeuXXF0dGTZsmVs377d5Kimvb093bp1Y+HChURFRRETE8OxY8cM248fP06LFi3M2ylCCFEK6/LugBCi8rl27Rq9evVi8ODBNGvWjCpVqnDw4EFmzZpF9+7dDXF169YlMjKStm3botVqqVq1Kt7e3mzYsIFu3bqhKAqTJk0q9tl+0dHRzJo1ix49ehAREcE333zDli1b7qi/devWJT09ncjISHx9fXFwcDAcoXvttdcMyWfhZzwWR6PREBgYyL59++jRoweQfxPPkCFDGDt2LNWrV8fNzY2JEyei0fzzN3idOnWwtbVl0aJFvP766xw/fpxp06aZ1G9lZUVwcDATJkzA29vb6JT7qlWryMvLw8/PDwcHB7744gvs7e2NHsWzd+9ennvuuTvaR0IIYaK8L4oUQlQ+mZmZ6vjx49WWLVuqLi4uqoODg9qwYUP13XffVTMyMgxx4eHhav369VVra2vVy8tLVdX8m0w6duyo2tvbq56enurixYvVDh06GN3k4eXlpYaGhqq9evVSHRwcVJ1Opy5YsMCoD1hw44qqqurrr7+uVq9eXQXUKVOmGNXVrl07tXHjxmaNfevWrWrt2rWNbg5JS0tT+/fvrzo4OKju7u7qrFmzTMa0du1atW7duqpWq1X9/f3V8PBwoz4XOHfunAqos2bNMlq/ceNG1c/PT3V2dlYdHR3Vp556St21a5dh+6VLl1QbGxv14sWLZo1DCCFKo6iqqpZnkiqEEOVJVVW8vb154403GD16tFnxfn5+/Pe//6VPnz5l3p+9e/fy7LPPcvHiRdzd3c0uN27cOJKTk1mxYkWZ90kI8XCSaxKFEA+tpKQkFi9eTEJCQonPRixKURRWrFhhcmfx3crKyuLSpUtMnTqVXr16WZQgAri5uRV7ClsIIe6UHEkUQjy0FEWhRo0aLFiwgL59+5ZrX1atWsWQIUNo3rw54eHh1K5du1z7I4QQkiQKIYQQQggTcrpZCCGEEEKYkCRRCCGEEEKYkCRRCCGEEEKYkCRRCCGEEEKYkCRRCCGEEEKYkCRRCCGEEEKYkCRRCCGEEEKYkCRRCCGEEEKYkCRRCCGEEEKY+H/AhrDZ4b0wdAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def to_percent(temp, position):\n",
    "    return '%1.0f' % (100 * temp) + '%'\n",
    "\n",
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "stability_calibration = pd.DataFrame(columns=['stability', 'predicted_retention', 'actual_retention'])\n",
    "stability_calibration = dataset[['stability', 'p', 'y']].copy()\n",
    "stability_calibration['bin'] = stability_calibration['stability'].map(lambda x: math.pow(1.2, math.floor(math.log(x, 1.2))))\n",
    "stability_group = stability_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=stability_group.index, height=stability_group['y'], width=stability_group.index / 5.5,\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Stability (days)\")\n",
    "ax1.semilogx()\n",
    "lns.append(lns1)\n",
    "\n",
    "stability_group = stability_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(stability_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(stability_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(1)\n",
    "ax1 = fig.add_subplot(111)\n",
    "ax2 = ax1.twinx()\n",
    "lns = []\n",
    "\n",
    "difficulty_calibration = pd.DataFrame(columns=['difficulty', 'predicted_retention', 'actual_retention'])\n",
    "difficulty_calibration = dataset[['difficulty', 'p', 'y']].copy()\n",
    "difficulty_calibration['bin'] = difficulty_calibration['difficulty'].map(round)\n",
    "difficulty_group = difficulty_calibration.groupby('bin').count()\n",
    "\n",
    "lns1 = ax1.bar(x=difficulty_group.index, height=difficulty_group['y'],\n",
    "                ec='k', lw=.2, label='Number of predictions', alpha=0.5)\n",
    "ax1.set_ylabel(\"Number of predictions\")\n",
    "ax1.set_xlabel(\"Difficulty\")\n",
    "lns.append(lns1)\n",
    "\n",
    "difficulty_group = difficulty_calibration.groupby(by='bin').agg('mean')\n",
    "lns2 = ax2.plot(difficulty_group['y'], label='Actual retention')\n",
    "lns3 = ax2.plot(difficulty_group['p'], label='Predicted retention')\n",
    "ax2.set_ylabel(\"Retention\")\n",
    "ax2.set_ylim(0, 1)\n",
    "lns.append(lns2[0])\n",
    "lns.append(lns3[0])\n",
    "\n",
    "labs = [l.get_label() for l in lns]\n",
    "ax2.legend(lns, labs, loc='lower right')\n",
    "plt.grid(linestyle='--')\n",
    "plt.gca().yaxis.set_major_formatter(ticker.FuncFormatter(to_percent))\n",
    "plt.gca().xaxis.set_major_formatter(ticker.FormatStrFormatter('%d'))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "#T_3ccbe_row2_col6, #T_3ccbe_row3_col4, #T_3ccbe_row5_col3 {\n",
       "  background-color: #ededff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row3_col3 {\n",
       "  background-color: #ff7d7d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row3_col5, #T_3ccbe_row4_col4, #T_3ccbe_row7_col1 {\n",
       "  background-color: #c5c5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row3_col6, #T_3ccbe_row7_col4, #T_3ccbe_row9_col3 {\n",
       "  background-color: #f9f9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row4_col3, #T_3ccbe_row12_col0 {\n",
       "  background-color: #ddddff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row4_col5 {\n",
       "  background-color: #b5b5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row4_col6, #T_3ccbe_row9_col4, #T_3ccbe_row12_col2, #T_3ccbe_row13_col2 {\n",
       "  background-color: #ffcdcd;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row5_col1, #T_3ccbe_row10_col4, #T_3ccbe_row13_col4 {\n",
       "  background-color: #e1e1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row5_col4, #T_3ccbe_row8_col0 {\n",
       "  background-color: #cdcdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row5_col5, #T_3ccbe_row13_col0 {\n",
       "  background-color: #c9c9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row5_col6 {\n",
       "  background-color: #ffc1c1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row6_col0, #T_3ccbe_row6_col5 {\n",
       "  background-color: #d9d9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row6_col1, #T_3ccbe_row7_col0, #T_3ccbe_row9_col1 {\n",
       "  background-color: #d5d5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row6_col2 {\n",
       "  background-color: #adadff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row6_col3 {\n",
       "  background-color: #ffd9d9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row6_col4 {\n",
       "  background-color: #f5f5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row6_col6 {\n",
       "  background-color: #ff8989;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row7_col3, #T_3ccbe_row10_col6 {\n",
       "  background-color: #ff7979;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row7_col6 {\n",
       "  background-color: #ff3131;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row8_col1 {\n",
       "  background-color: #f1f1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row8_col2, #T_3ccbe_row11_col2 {\n",
       "  background-color: #ffeded;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row8_col3, #T_3ccbe_row10_col3, #T_3ccbe_row11_col5 {\n",
       "  background-color: #ff9d9d;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row8_col4 {\n",
       "  background-color: #fff1f1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row8_col5 {\n",
       "  background-color: #ffc5c5;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row8_col6 {\n",
       "  background-color: #ff0101;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row9_col0 {\n",
       "  background-color: #bdbdff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row9_col2, #T_3ccbe_row12_col4 {\n",
       "  background-color: #fff9f9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row9_col5 {\n",
       "  background-color: #ffa9a9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row9_col6 {\n",
       "  background-color: #e60000;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row10_col0, #T_3ccbe_row14_col2 {\n",
       "  background-color: #c1c1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row10_col1, #T_3ccbe_row10_col5 {\n",
       "  background-color: #ffe9e9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row10_col2 {\n",
       "  background-color: #ffc9c9;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row11_col0 {\n",
       "  background-color: #b1b1ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row11_col1 {\n",
       "  background-color: #e9e9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row11_col3 {\n",
       "  background-color: #ff8585;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row11_col4 {\n",
       "  background-color: #ffa1a1;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row12_col1 {\n",
       "  background-color: #e5e5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row12_col3 {\n",
       "  background-color: #ff6d6d;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row12_col5 {\n",
       "  background-color: #8d8dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row13_col1 {\n",
       "  background-color: #a5a5ff;\n",
       "  color: #000000;\n",
       "}\n",
       "#T_3ccbe_row14_col0, #T_3ccbe_row14_col1 {\n",
       "  background-color: #8181ff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row15_col0 {\n",
       "  background-color: #9d9dff;\n",
       "  color: #f1f1f1;\n",
       "}\n",
       "#T_3ccbe_row15_col1 {\n",
       "  background-color: #a9a9ff;\n",
       "  color: #000000;\n",
       "}\n",
       "</style>\n",
       "<table id=\"T_3ccbe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >d_bin</th>\n",
       "      <th id=\"T_3ccbe_level0_col0\" class=\"col_heading level0 col0\" >3</th>\n",
       "      <th id=\"T_3ccbe_level0_col1\" class=\"col_heading level0 col1\" >5</th>\n",
       "      <th id=\"T_3ccbe_level0_col2\" class=\"col_heading level0 col2\" >6</th>\n",
       "      <th id=\"T_3ccbe_level0_col3\" class=\"col_heading level0 col3\" >7</th>\n",
       "      <th id=\"T_3ccbe_level0_col4\" class=\"col_heading level0 col4\" >8</th>\n",
       "      <th id=\"T_3ccbe_level0_col5\" class=\"col_heading level0 col5\" >9</th>\n",
       "      <th id=\"T_3ccbe_level0_col6\" class=\"col_heading level0 col6\" >10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th class=\"index_name level0\" >s_bin</th>\n",
       "      <th class=\"blank col0\" >&nbsp;</th>\n",
       "      <th class=\"blank col1\" >&nbsp;</th>\n",
       "      <th class=\"blank col2\" >&nbsp;</th>\n",
       "      <th class=\"blank col3\" >&nbsp;</th>\n",
       "      <th class=\"blank col4\" >&nbsp;</th>\n",
       "      <th class=\"blank col5\" >&nbsp;</th>\n",
       "      <th class=\"blank col6\" >&nbsp;</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row0\" class=\"row_heading level0 row0\" >1.000000</th>\n",
       "      <td id=\"T_3ccbe_row0_col0\" class=\"data row0 col0\" ></td>\n",
       "      <td id=\"T_3ccbe_row0_col1\" class=\"data row0 col1\" ></td>\n",
       "      <td id=\"T_3ccbe_row0_col2\" class=\"data row0 col2\" ></td>\n",
       "      <td id=\"T_3ccbe_row0_col3\" class=\"data row0 col3\" ></td>\n",
       "      <td id=\"T_3ccbe_row0_col4\" class=\"data row0 col4\" ></td>\n",
       "      <td id=\"T_3ccbe_row0_col5\" class=\"data row0 col5\" ></td>\n",
       "      <td id=\"T_3ccbe_row0_col6\" class=\"data row0 col6\" >4.86%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row1\" class=\"row_heading level0 row1\" >1.400000</th>\n",
       "      <td id=\"T_3ccbe_row1_col0\" class=\"data row1 col0\" ></td>\n",
       "      <td id=\"T_3ccbe_row1_col1\" class=\"data row1 col1\" ></td>\n",
       "      <td id=\"T_3ccbe_row1_col2\" class=\"data row1 col2\" ></td>\n",
       "      <td id=\"T_3ccbe_row1_col3\" class=\"data row1 col3\" ></td>\n",
       "      <td id=\"T_3ccbe_row1_col4\" class=\"data row1 col4\" ></td>\n",
       "      <td id=\"T_3ccbe_row1_col5\" class=\"data row1 col5\" >2.55%</td>\n",
       "      <td id=\"T_3ccbe_row1_col6\" class=\"data row1 col6\" >1.67%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row2\" class=\"row_heading level0 row2\" >1.960000</th>\n",
       "      <td id=\"T_3ccbe_row2_col0\" class=\"data row2 col0\" ></td>\n",
       "      <td id=\"T_3ccbe_row2_col1\" class=\"data row2 col1\" ></td>\n",
       "      <td id=\"T_3ccbe_row2_col2\" class=\"data row2 col2\" ></td>\n",
       "      <td id=\"T_3ccbe_row2_col3\" class=\"data row2 col3\" ></td>\n",
       "      <td id=\"T_3ccbe_row2_col4\" class=\"data row2 col4\" >1.72%</td>\n",
       "      <td id=\"T_3ccbe_row2_col5\" class=\"data row2 col5\" >-4.71%</td>\n",
       "      <td id=\"T_3ccbe_row2_col6\" class=\"data row2 col6\" >-0.72%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row3\" class=\"row_heading level0 row3\" >2.740000</th>\n",
       "      <td id=\"T_3ccbe_row3_col0\" class=\"data row3 col0\" ></td>\n",
       "      <td id=\"T_3ccbe_row3_col1\" class=\"data row3 col1\" ></td>\n",
       "      <td id=\"T_3ccbe_row3_col2\" class=\"data row3 col2\" ></td>\n",
       "      <td id=\"T_3ccbe_row3_col3\" class=\"data row3 col3\" >5.11%</td>\n",
       "      <td id=\"T_3ccbe_row3_col4\" class=\"data row3 col4\" >-0.65%</td>\n",
       "      <td id=\"T_3ccbe_row3_col5\" class=\"data row3 col5\" >-2.28%</td>\n",
       "      <td id=\"T_3ccbe_row3_col6\" class=\"data row3 col6\" >-0.27%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row4\" class=\"row_heading level0 row4\" >3.840000</th>\n",
       "      <td id=\"T_3ccbe_row4_col0\" class=\"data row4 col0\" ></td>\n",
       "      <td id=\"T_3ccbe_row4_col1\" class=\"data row4 col1\" ></td>\n",
       "      <td id=\"T_3ccbe_row4_col2\" class=\"data row4 col2\" ></td>\n",
       "      <td id=\"T_3ccbe_row4_col3\" class=\"data row4 col3\" >-1.40%</td>\n",
       "      <td id=\"T_3ccbe_row4_col4\" class=\"data row4 col4\" >-2.28%</td>\n",
       "      <td id=\"T_3ccbe_row4_col5\" class=\"data row4 col5\" >-2.93%</td>\n",
       "      <td id=\"T_3ccbe_row4_col6\" class=\"data row4 col6\" >1.95%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row5\" class=\"row_heading level0 row5\" >5.380000</th>\n",
       "      <td id=\"T_3ccbe_row5_col0\" class=\"data row5 col0\" ></td>\n",
       "      <td id=\"T_3ccbe_row5_col1\" class=\"data row5 col1\" >-1.10%</td>\n",
       "      <td id=\"T_3ccbe_row5_col2\" class=\"data row5 col2\" ></td>\n",
       "      <td id=\"T_3ccbe_row5_col3\" class=\"data row5 col3\" >-0.74%</td>\n",
       "      <td id=\"T_3ccbe_row5_col4\" class=\"data row5 col4\" >-2.01%</td>\n",
       "      <td id=\"T_3ccbe_row5_col5\" class=\"data row5 col5\" >-2.09%</td>\n",
       "      <td id=\"T_3ccbe_row5_col6\" class=\"data row5 col6\" >2.41%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row6\" class=\"row_heading level0 row6\" >7.530000</th>\n",
       "      <td id=\"T_3ccbe_row6_col0\" class=\"data row6 col0\" >-1.47%</td>\n",
       "      <td id=\"T_3ccbe_row6_col1\" class=\"data row6 col1\" >-1.69%</td>\n",
       "      <td id=\"T_3ccbe_row6_col2\" class=\"data row6 col2\" >-3.23%</td>\n",
       "      <td id=\"T_3ccbe_row6_col3\" class=\"data row6 col3\" >1.45%</td>\n",
       "      <td id=\"T_3ccbe_row6_col4\" class=\"data row6 col4\" >-0.44%</td>\n",
       "      <td id=\"T_3ccbe_row6_col5\" class=\"data row6 col5\" >-1.48%</td>\n",
       "      <td id=\"T_3ccbe_row6_col6\" class=\"data row6 col6\" >4.66%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row7\" class=\"row_heading level0 row7\" >10.540000</th>\n",
       "      <td id=\"T_3ccbe_row7_col0\" class=\"data row7 col0\" >-1.61%</td>\n",
       "      <td id=\"T_3ccbe_row7_col1\" class=\"data row7 col1\" >-2.27%</td>\n",
       "      <td id=\"T_3ccbe_row7_col2\" class=\"data row7 col2\" ></td>\n",
       "      <td id=\"T_3ccbe_row7_col3\" class=\"data row7 col3\" >5.29%</td>\n",
       "      <td id=\"T_3ccbe_row7_col4\" class=\"data row7 col4\" >-0.21%</td>\n",
       "      <td id=\"T_3ccbe_row7_col5\" class=\"data row7 col5\" >1.80%</td>\n",
       "      <td id=\"T_3ccbe_row7_col6\" class=\"data row7 col6\" >8.03%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row8\" class=\"row_heading level0 row8\" >14.760000</th>\n",
       "      <td id=\"T_3ccbe_row8_col0\" class=\"data row8 col0\" >-2.02%</td>\n",
       "      <td id=\"T_3ccbe_row8_col1\" class=\"data row8 col1\" >-0.52%</td>\n",
       "      <td id=\"T_3ccbe_row8_col2\" class=\"data row8 col2\" >0.63%</td>\n",
       "      <td id=\"T_3ccbe_row8_col3\" class=\"data row8 col3\" >3.77%</td>\n",
       "      <td id=\"T_3ccbe_row8_col4\" class=\"data row8 col4\" >0.61%</td>\n",
       "      <td id=\"T_3ccbe_row8_col5\" class=\"data row8 col5\" >2.30%</td>\n",
       "      <td id=\"T_3ccbe_row8_col6\" class=\"data row8 col6\" >9.90%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row9\" class=\"row_heading level0 row9\" >20.660000</th>\n",
       "      <td id=\"T_3ccbe_row9_col0\" class=\"data row9 col0\" >-2.55%</td>\n",
       "      <td id=\"T_3ccbe_row9_col1\" class=\"data row9 col1\" >-1.69%</td>\n",
       "      <td id=\"T_3ccbe_row9_col2\" class=\"data row9 col2\" >0.26%</td>\n",
       "      <td id=\"T_3ccbe_row9_col3\" class=\"data row9 col3\" >-0.31%</td>\n",
       "      <td id=\"T_3ccbe_row9_col4\" class=\"data row9 col4\" >1.98%</td>\n",
       "      <td id=\"T_3ccbe_row9_col5\" class=\"data row9 col5\" >3.36%</td>\n",
       "      <td id=\"T_3ccbe_row9_col6\" class=\"data row9 col6\" >12.01%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row10\" class=\"row_heading level0 row10\" >28.930000</th>\n",
       "      <td id=\"T_3ccbe_row10_col0\" class=\"data row10 col0\" >-2.40%</td>\n",
       "      <td id=\"T_3ccbe_row10_col1\" class=\"data row10 col1\" >0.86%</td>\n",
       "      <td id=\"T_3ccbe_row10_col2\" class=\"data row10 col2\" >2.15%</td>\n",
       "      <td id=\"T_3ccbe_row10_col3\" class=\"data row10 col3\" >3.87%</td>\n",
       "      <td id=\"T_3ccbe_row10_col4\" class=\"data row10 col4\" >-1.16%</td>\n",
       "      <td id=\"T_3ccbe_row10_col5\" class=\"data row10 col5\" >0.89%</td>\n",
       "      <td id=\"T_3ccbe_row10_col6\" class=\"data row10 col6\" >5.23%</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row11\" class=\"row_heading level0 row11\" >40.500000</th>\n",
       "      <td id=\"T_3ccbe_row11_col0\" class=\"data row11 col0\" >-3.09%</td>\n",
       "      <td id=\"T_3ccbe_row11_col1\" class=\"data row11 col1\" >-0.87%</td>\n",
       "      <td id=\"T_3ccbe_row11_col2\" class=\"data row11 col2\" >0.66%</td>\n",
       "      <td id=\"T_3ccbe_row11_col3\" class=\"data row11 col3\" >4.83%</td>\n",
       "      <td id=\"T_3ccbe_row11_col4\" class=\"data row11 col4\" >3.70%</td>\n",
       "      <td id=\"T_3ccbe_row11_col5\" class=\"data row11 col5\" >3.75%</td>\n",
       "      <td id=\"T_3ccbe_row11_col6\" class=\"data row11 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row12\" class=\"row_heading level0 row12\" >56.690000</th>\n",
       "      <td id=\"T_3ccbe_row12_col0\" class=\"data row12 col0\" >-1.31%</td>\n",
       "      <td id=\"T_3ccbe_row12_col1\" class=\"data row12 col1\" >-1.01%</td>\n",
       "      <td id=\"T_3ccbe_row12_col2\" class=\"data row12 col2\" >1.96%</td>\n",
       "      <td id=\"T_3ccbe_row12_col3\" class=\"data row12 col3\" >5.65%</td>\n",
       "      <td id=\"T_3ccbe_row12_col4\" class=\"data row12 col4\" >0.16%</td>\n",
       "      <td id=\"T_3ccbe_row12_col5\" class=\"data row12 col5\" >-4.48%</td>\n",
       "      <td id=\"T_3ccbe_row12_col6\" class=\"data row12 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row13\" class=\"row_heading level0 row13\" >79.370000</th>\n",
       "      <td id=\"T_3ccbe_row13_col0\" class=\"data row13 col0\" >-2.15%</td>\n",
       "      <td id=\"T_3ccbe_row13_col1\" class=\"data row13 col1\" >-3.47%</td>\n",
       "      <td id=\"T_3ccbe_row13_col2\" class=\"data row13 col2\" >1.93%</td>\n",
       "      <td id=\"T_3ccbe_row13_col3\" class=\"data row13 col3\" ></td>\n",
       "      <td id=\"T_3ccbe_row13_col4\" class=\"data row13 col4\" >-1.12%</td>\n",
       "      <td id=\"T_3ccbe_row13_col5\" class=\"data row13 col5\" ></td>\n",
       "      <td id=\"T_3ccbe_row13_col6\" class=\"data row13 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row14\" class=\"row_heading level0 row14\" >111.120000</th>\n",
       "      <td id=\"T_3ccbe_row14_col0\" class=\"data row14 col0\" >-4.98%</td>\n",
       "      <td id=\"T_3ccbe_row14_col1\" class=\"data row14 col1\" >-4.87%</td>\n",
       "      <td id=\"T_3ccbe_row14_col2\" class=\"data row14 col2\" >-2.41%</td>\n",
       "      <td id=\"T_3ccbe_row14_col3\" class=\"data row14 col3\" ></td>\n",
       "      <td id=\"T_3ccbe_row14_col4\" class=\"data row14 col4\" ></td>\n",
       "      <td id=\"T_3ccbe_row14_col5\" class=\"data row14 col5\" ></td>\n",
       "      <td id=\"T_3ccbe_row14_col6\" class=\"data row14 col6\" ></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th id=\"T_3ccbe_level0_row15\" class=\"row_heading level0 row15\" >155.570000</th>\n",
       "      <td id=\"T_3ccbe_row15_col0\" class=\"data row15 col0\" >-3.78%</td>\n",
       "      <td id=\"T_3ccbe_row15_col1\" class=\"data row15 col1\" >-3.42%</td>\n",
       "      <td id=\"T_3ccbe_row15_col2\" class=\"data row15 col2\" ></td>\n",
       "      <td id=\"T_3ccbe_row15_col3\" class=\"data row15 col3\" ></td>\n",
       "      <td id=\"T_3ccbe_row15_col4\" class=\"data row15 col4\" ></td>\n",
       "      <td id=\"T_3ccbe_row15_col5\" class=\"data row15 col5\" ></td>\n",
       "      <td id=\"T_3ccbe_row15_col6\" class=\"data row15 col6\" ></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2d0f92850>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "B_W_Metric_raw = dataset[['difficulty', 'stability', 'p', 'y']].copy()\n",
    "B_W_Metric_raw['s_bin'] = B_W_Metric_raw['stability'].map(lambda x: round(math.pow(1.4, math.floor(math.log(x, 1.4))), 2))\n",
    "B_W_Metric_raw['d_bin'] = B_W_Metric_raw['difficulty'].map(lambda x: int(round(x)))\n",
    "B_W_Metric = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('mean').reset_index()\n",
    "B_W_Metric_count = B_W_Metric_raw.groupby(by=['s_bin', 'd_bin']).agg('count').reset_index()\n",
    "B_W_Metric['B-W'] = B_W_Metric['p'] - B_W_Metric['y']\n",
    "n = len(dataset)\n",
    "bins = len(B_W_Metric)\n",
    "B_W_Metric_pivot = B_W_Metric[B_W_Metric_count['p'] > max(50, n / (3 * bins))].pivot(index=\"s_bin\", columns='d_bin', values='B-W')\n",
    "B_W_Metric_pivot.apply(pd.to_numeric).style.background_gradient(cmap='seismic', axis=None, vmin=-0.2, vmax=0.2).format(\"{:.2%}\", na_rep='')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R_Metric:  0.04011419275176281\n",
      "R-squared: -6.8749\n",
      "RMSE: 0.1527\n",
      "[0.68927589 0.25115013]\n"
     ]
    },
    {
     "data": {
      "image/png": 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qFe+99x7r1q2jd+/eREVF0bJlS+zt7a3P6dix7P1JSzqfAtq0aWOzfeLECU6cOGETIiBJEmazmYsXL5b7OuzZsweNRsOBAwd47733WLx4sfWxiIgITpw4wYoVK4o85pkzZ1AqlbRufSOIv2HDhri7F67jduv5REREsHfvXhsLtslkIi8vj5ycHIYPH86nn35qPZ8BAwYwaNAglEplmc41KioKpVJp87719PQkODiYqKgo6z6NRmMTl1uaz8y9gr2jM44ubpUzmdkEexbCzvdAMoNXYxi+HHyblerpGbkGNp6MY/Wxqxy+lGbdr1ErKmd9gmIRAlBQo9CoNGhf01bbsUtLw4YNqV27Nv/++y9paWl069YNgICAAAIDA9m3bx///vsvDz30EGARAgAbNmygVq1aNnPZ2dlVaN0qlcpmWyaTlei+0Wq1DBo0iA8++MC6r6D/bKNGjbhw4UKF1nS7Y94aO1lAQSzdrFmz2LZtGx9//DENGzbEwcGBYcOGWRMVnJ2dOXbsGDt37mTr1q28/fbbzJkzh8OHD5c5+9jZ2ZlBgwYxaNAg3nnnHfr27cs777xTSKTfDrlcXihs4NaEh5LOpwBHR0ebba1Wy/jx43nxxRcLtYKrU6cOarW6XNehXr16uLm5ERwcTGJiIiNGjGD37t3WY/7vf/+zib27+Zhnzpwp8ZoUdz5z587l0UcfLTTW3t6ewMBAYmJi+Oeff9i2bRvPPfccH330Ebt27arU17yAoj4zt76WghLQJsLqyXBhp2U7dBQM+BjsCv+ovBmDycyes0n8eewa2yIT0Bst31UyGTzY0ItHW9eibzM/NGohT6oacYUFNQqZTIaj2rHkgTWAHj16sHPnTtLS0njppZes+7t27cqmTZs4dOgQzz77LABNmzbFzs6OK1euWMViSQQHB3P48GGbfbdulwa1Wl0o1q1169b8+eefBAUFoVRavgbMZjOZmZk4OjrSoEEDVCoVBw8epE6dOoAluP7MmTOlXv+ttG7dmvj4eJRKJUFBQUWO2bt3L+PHj7daPrVabaFEDqVSSa9evejVqxezZ8/Gzc2NHTt28OijjxZ5rqVBJpMREhLCvn37AGjSpAk//fQTeXl5Vivgzck9YIklzMrKIjs72yp4ChJEynI+RREWFkZMTAwNGza8bS/g4q5DaZgyZQoLFixgzZo1DB06lNatWxMZGUnDhg2LHB8cHIzRaOT48eM88MADAJw7d460tLQix99M69atredzOxwcHKyCfMqUKYSEhHDy5Elat25d6nNt0qQJRqORgwcP0qlTJwBSUlKIiYmhadOmpbouglJwYZdF/GkTQKWxCL+wMbcdLkkSp69nsvrYNdZFXCNZe+MHUGNfJx5tXZshrWrh52p/2zkElY8QgAJBOenRowdTpkzBYDDYiKJu3boxdepU9Hq9NQHE2dmZWbNmMWPGDMxmMw8++CAZGRns3bsXFxcXxo0bV2j+559/nq5du7Jw4UIGDRrEjh072LRpU5nLxAQFBXHw4EEuXbqEk5MTHh4eTJkyhW+//ZZRo0bx8ssv4+HhwZkzZ/j5559Zvnw5Tk5OTJo0iZdeeglPT098fHx44403bitGbsZkMhUSQnZ2dvTq1YuOHTsyZMgQPvzwQxo3bsz169fZsGEDQ4cOpU2bNjRq1IjVq1czaNAgZDIZb731lo01c/369Vy4cIGuXbvi7u7Oxo0bMZvNVtd0Ued665rDw8OZPXs2Tz75JE2bNkWtVrNr1y6WLl3KK6+8AsDo0aN54403mDx5Mq+99hqXLl3i448/tpmnffv2aDQaXn/9daZNm8bBgwdZvny5zZiSzud2vPzyy3Tq1Innn3+eyZMn4+joSGRkJNu2beOLL74o8TqUBo1Gw+TJk5k9ezZDhgzhlVdeoUOHDkydOpWnnnqq0DFDQkLo1asXTz/9NF9//TUqlYoXX3wRBweHEt+Tb7/9Ng8//DB16tRh2LBhyOVyIiIiOHXqFO+88w7Lly/HZDJZr+nPP/+Mg4MDdevWLdO5NmrUiMGDBzN58mS++eYbnJ2defXVV6lVqxaDBw8u9bUR3AazCXZ9ALs+BCTwbmJx+fqEWIdIkkSSVkd0XBbR8ZlEx2URfjWdC0k3ssm9nNQ8ElqLR1vXolmACzKZjHhtPJvPhRMRH0F4Qjh96vdhQtiEwmsQVBpCAAoE5aRHjx7k5uYSEhKCr6+vdX+3bt3IysqylospYP78+Xh7e7NgwQIuXLiAm5sbrVu35vXXXy9y/s6dO7N48WLmzp3Lm2++Sd++fZkxYwZffPFFmdY5a9Ysxo0bR9OmTcnNzeXixYsEBQWxd+9eXnnlFfr06YNOp6Nu3br06NHDKpg++ugjq6vY2dmZF198kYyMjBKPp9VqC8U1NmjQgHPnzrFx40beeOMNJkyYQFJSEn5+fnTt2tV6/RYuXMjEiRPp1KkTXl5evPLKK2RmZlrncXNzY/Xq1cyZM4e8vDwaNWrEL7/8QrNmzYo915upXbs2QUFBzJ07l0uXLiGTyazbM2bMAMDJyYm///6bZ555hrCwMJo2bcoHH3zAY489Zp3Hw8ODn3/+mZdeeolvv/2Wnj17MmfOHGsZl9Kcz+1o2bIl69evZ8GCBXTp0gVJkmjQoAEjRowo1XUoLVOnTmXhwoWsWrWKxx9/nF27dvHGG28UeUyAH3/8kUmTJtG1a1f8/PxYsGABp0+ftomVLIq+ffuyfv165s2bxwcffIBKpSIkJISnnnrKej7vv/8+M2fOxGQy0aJFC/7++288PT3LfK7Lli3jhRde4OGHH0av19O1a1c2btxYyO0rKCOZcRar36U9lu2wJ8nrvYBzaWaijsQSHX9D8KVkF64tqVbK6dPUlyFhAfh5pHEqKYKfo34k/N9wwuPDSchOsBkvQyYEYBUjk+6zwIerV68SGBhY5I1BcGfJysrizJkzNGnSpMxB/PcrkydPJjo6mj179lT63AUuYBcXl1JZ+u43Ll26RL169Th+/HiVt9+7W16Lgu/Tf/75h549e1b3cqqEnJwcoqKiaNy48V1fcDo1NZWv/j1XbBKI0WQmOTWVh1v4Y1Q7kqrVY39lJ91Pv4mjMY08mT1fOT3PGlMnrqXlYi5CQchlUM/LkYa+GlwdtZjkV0gzHyYy5SgnEk6Qa8wt9BwZMoK9gmnl14pWvq14sM6DdK7T2WZMwWcwNjaW2rVrV/Ry3PcIC6BAUIP5+OOP6d27N46OjmzatIkffviBr776qrqXJbhP2bFjB1qtlhYtWhAXF8fLL79MUFBQmWoQCqoXrc5I9OVUcvUmcgwmcvUmm38bzRKm3CxWHryC2kHDDOUfPKdYh1wmEWmuyxTDNC7m+gMWEeeuUdHE34VATwVquySypTPE5hziROJR/j1/FonCClGj0tDStyWtfFtZBJ9fK5r7NL9r4r/vFYQAFAhqMIcOHeLDDz8kKyuL+vXr89lnn1ndZgLBncZgMPD6669z4cIFnJ2d6dSpEytWrBDu1buE9Gw9q49dRa8sXmjJZRDimM0nDotobowE4IjXUI6EzOIpZyfyzEkk5l4gLucU0WmH2J4QTuL1osvo+Dn5EeobSphfmFXsNfRoiEIuSr1UN0IACgQ1mN9//726lyDIJygo6L4vFdK3b1/69u1b3csQlJNP/zlLrsGMu5OSBt5OOKgVaNQKHFQKm38brp3gudi5eBgzMKoc2N58CH/KzYRfnMjJxJPkGfMKzS2XyQn2DLaKvFZ+rQj1DcXXybeIlQhqAkIACgQCgUBwj3PoYiprwq8B0K+5H/6uDjc9KpGlyyJBewX7K4dwj78AqnSOOpgZYUjkfPg3NnM5qhxp6dvSYtnzD7O6cMtSS1VQ/QgBKBAIBALBPYzeaOb1NScBCPFzQqnM4mTCOeK18cRnxxOvjUelz2EYKmojJxv4Bh1z0OPlEsCA/MSMVn6tCPULpYF7A+HCvQcQAlAgEAgEgnuQLF0WJxJOsHjnRc4luiOT53A0ZQOHj9jWogyW5AxGjQMyDDI5Z72DeaTPSmJDuuDj6FNNqxdUNUIACgQCgUBwFyNJEteyrhEeH27zdz7tPEqzH/66L5EDKYqlKCQ/7BXO+Dr6EuDoS+vcDHzS8ntTO/ujajaYRnroUa8hHo4e1XpegqpFCECBQCAQCO4SDCYDMSkxhcReSm5K4cESBEgzkGGHn0cGsx98isiL/vj7BCHLTYfIvyAr3jI2sB3U6wZyBejT7+QpCaoJIQAFAoFAIKiBZOoyOZFwwkbonUo8hc6kKzRWIVMQ4hViScrIj9dLSKnN63+eQ62Qs3LCI7gp9FyLO4cs6QzEbASjDpT20GQgeDaqhjMUVCdCAAoE9yAymYw1a9YwZMiQKj3O8uXLmT59Ounp6QDMmTOHtWvXWnsBjx8/nvT0dNauXVul67iZoKAgpk+fzvTp0+/YMQWVi95oJiVbh5eTHSpFze2EUllIksTVzKs3hF6CpSfu+bTzRY53VjsT6hdqU0i5mU8z7JU3WvJl5BrouXIXAM/1aEB9bydSE67DhX8hPcYyyLUWNHkE7F2r/BwFNQ8hAAWCCrB//34efPBB+vXrx4YNG8r03OoWKvHx8bz77rts2LCBa9eu4ePjQ7NmzXjxxRfp3bt3ueacNWsWzz//fCWvtGhuFZ8FHD58GEdH0VHgbiZJqyNFq0NvNFPX8956LQ0mA1HJUYTHW0ReeIJF9KXmphY5vrZLbcL8wgj1DbWKvXru9ZDLihfGH22JJlmro76XI892bwAp5+HnMRDXABzsoE4HqNcFZCKb935FCECBoAJ8//33PP/883z//fdcv36dgICA6l5Sqbh06RKdO3fGzc2Njz76iBYtWqDT6Vi3bh3PP/880dHR5ZrXyckJJyenCq1Nr9ejVqvL/Xxvb+8KHV9Q/eQZTABk5hrRG82olXenFTAjL4OIhAgbF+7ppNPoTfpCY5VyJU28mhQqpOyp8SzzcY9fSWPFQUtixztDm2MXtQb+ng4ZmaBqBi2HgUeDip6e4C7n7vxUCQQ1AK1Wy2+//cazzz7LwIEDWb58eaExf//9N23btsXe3h4vLy+GDh0KQPfu3bl8+TIzZsxAJpMhk8kAiwu1VatWNnN8+umnBAUFWbcPHz5M79698fLywtXVlW7dunHs2LEyrf25555DJpNx6NAhHnvsMRo3bkyzZs2YMmUK+/bts45buHAhLVq0wNHRkcDAQJ577jm0Wu1t5y1q/QBz587F29sbFxcXnnnmGfT6GzfA7t27M3XqVKZPn46Xl5e100Rxx965cycTJkwgIyPDev3mzJkDWCyrn376qXX+K1euMHjwYJycnHBxceHxxx8nISGh0Jp/+ukngoKCcHV1ZeTIkWRlZZXpmgoqD53BUqZEQiI1u3C8W01DkiQup1/mr+i/mLtzLkN/G0q9RfVw+8CNbsu78cLmF1gWvozj8cfRm/S42LnQtW5XprWbxtJHlnLs6WNoX9Ny4tkT/Dj0R2Z2nMlD9R4ql/gzmsy8vuYUkgQjWnnRKXI+/DkJ9FlQqy20GiPEnwAQAlBQw5AkiRy9sVr+ytrm6/fffyckJITg4GCeeOIJli5dajPHhg0bGDp0KAMGDOD48eNs376ddu3aAbB69Wpq167NvHnziIuLIy4urtTHzcrKYty4cfz3338cOHCARo0aMWDAgFILltTUVDZv3syUKVOKdJW6ublZ/y2Xy/nss884ffo0P/zwAzt27ODll18u9VoBtm/fTlRUFDt37uSXX35h9erVzJ0712bMDz/8gFqtZu/evSxevLjEY3fq1IlPP/0UFxcX6/WbNWtWoWObzWYGDx5Mamoqu3btYtu2bVy4cIERI0bYjDt//jxr165l/fr1rF+/nl27dvH++++X6TwFlYPRZMZovlGnLjVbj9lcc1rw6U16wuPD+SH8B2ZsnkGPH3rg8aEHQYuCGPLbEObsmsPa6LVcSr8EQF3XujwS/Ahvd32b1Y+v5vy086S/ks6u8btY1H8RE8ImEOYfhp3SrlLWt2zvJaLiMmnlkMi7yS/A0eWADLq+BKN+AXXFLPR3G7t372bQoEEEBAQgk8kKxSMX/IC89e+jjz6yjgkKCir0+K3fDydOnKBLly7Y29sTGBjIhx9+WGgtq1atIiQkBHt7e1q0aMHGjRur5JxLi3ABC2oUuQYTTd/eUi3HjpzXF4269B+J77//nieeeAKAfv36kZGRwa5du+jevTsA7777LiNHjrQRO6GhoQB4eHigUChwdnbGz8+vTOt86KGHbLaXLFmCm5sbu3bt4uGHHy7x+efOnUOSJEJCQkoce3N8YlBQEO+88w7PPPMMX331VanXq1arWbp0KRqNhmbNmjFv3jxeeukl5s+fj1xu+Q3aqFGjQl+YxR1brVbj6uqKTCYr9vpt376dkydPcvHiRQIDAwH48ccfadasGYcPH6Zt27aARSguX74cZ2dnAJ588km2b9/Ou+++W+rzFFQOOqNF/KkUcmSA3mQmPVePh2PlCKSyYDQbyTHkkGvK5c1/32TX9V1EJkViMBtAAmQ3xirlSpp5N7Nx4bb0bYmHw52rpXctPZeF284wVL6HD+XLUSbngqM3PLoEGjwEqUXHGd7LZGdnExoaysSJE3n00UcLPX7rj+9NmzYxadIkHnvsMZv98+bNY/Lkydbtgu8KgMzMTPr06UOvXr1YvHgxJ0+eZOLEibi5ufH0008DsG/fPkaNGsWCBQt4+OGHWblyJUOGDOHYsWM0b968Mk+51AgBKBCUg5iYGA4dOsSaNWsAUCqVjBgxgu+//94qAMPDw22+MCqLhIQE3nzzTXbu3EliYiImk4mcnByuXLlSqueXxdL5zz//sGDBAqKjo8nMzMRoNJKXl0dOTg4aTen6foaGhtqM7dixI1qtltjYWOrWrQvAAw88UCXHjoqKIjAw0Cr+AJo2bYqbmxtRUVFWARgUFGTzhe7v709iYmKpjiGoXAri/+xVCpzsFMRl5JGs1eOuUVtDJSobSZLQm/QWsWfMJceQQ44hxxKrZwStSctfZ/7icvZlADwULXHLex1/z0zGd1XRplYrmng1qTQrXlnI1ZtIz9WTlm1g0abjzJW+4nH1LjABQV3gse/AuWw/Mu8l+vfvT//+/W/7+K0/IP/66y969OhB/fr1bfYX92N9xYoV6PV6li5dilqtplmzZoSHh7Nw4UKrAFy0aBH9+vXjpZdeAmD+/Pls27aNL774wur1uNMIASioUTioFETO61ttxy4t33//PUaj0SbpQ5Ik7Ozs+OKLL3B1dcXBwaGYGYpGLpcXEmgGg8Fme9y4caSkpLBo0SLq1q2LnZ0dHTt2tImrK45GjRohk8lKTPS4dOkSDz/8MM8++yzvvvsuHh4e/Pfff0yaNAm9Xl9qEVYabnVF38ljA6hUKpttmUyG2Wy+zWhBVVJgAbRTynHXqEnI1JFnMJGtM+FkX/Fbllkyk2fII8doEXm5BovgM0mmIser5CrUcjXPtXmOxn6NCfUN5eXf4jh8KY2rCU4cOOXLk6EtsFNWfjbtqWsZ/HcumfQcA+k5etJzDKTl6MnItfw/PcdgvV6NZFf5UrWIxsprSDI5sm6vQtdZlsLOglKRkJDAhg0b+OGHHwo99v777zN//nzq1KnD6NGjmTFjBkql5f24f/9+unbtapO81rdvXz744APS0tJwd3dn//79zJw502bOvn373tESWbciBKCgRiGTycrkhq0OjEYjP/74I5988gl9+vSxeWzIkCH88ssvPPPMM7Rs2ZLt27czYcKEIudRq9WYTLY3HW9vb+Lj45EkyWrtKKipV8DevXv56quvGDBgAACxsbEkJyeXev0eHh707duXL7/8kmnTphUSX+np6Xh4eHD06FHMZjOffPKJ1VX7+++/l/o4BURERJCbm2sVxAcOHMDJycnGKncrpTl2UdfvVpo0aUJsbCyxsbHW40VGRpKenk7Tpk3LfC6CqueGBVCOUiHHXaMiJVtPSrauzALQ6sI13LDq5RnzkChsBZchw15pj0atQaPUoFFpcFA5oM/TY0ww8uwDz+Ls7MzW0/EcvpRmzUz+JyqBZ38+xtdPtK5UEbjhRBwv/HocY4nxjxIjlbuYo1yOPXpy7LzRjFxmKfFyj5KVlUVmZqZ1287ODju7iltff/jhB5ydnQu5iqdNm0br1q3x8PBg3759vPbaa8TFxbFw4ULAUlKrXr16Ns/x9fW1Pubu7k58fLx1381j4uPjK7zu8lKz77QCQQ1k/fr1pKWlMWnSJFxdbQuoPvbYY3z//fc888wzzJ49m549e9KgQQNGjhyJ0Whk48aNvPLKK4DF7bh7925GjhyJnZ0dXl5edO/enaSkJD788EOGDRvG5s2b2bRpEy4uLtZjNGrUiJ9++ok2bdqQmZnJSy+9VGZr45dffknnzp1p164d8+bNo2XLluj1etavX8/y5cuJioqiYcOGGAwGPv/8cwYNGmSToFEW9Ho9kyZN4s033+TSpUvMnj2bqVOnWoVdUZTm2EFBQWi1WrZv3251M99qGezVqxctWrRgzJgxfPrppxiNRp577jm6detGmzZtynwugqrnhgXQIqY8nexIydaTmWtAbzShLkJk3ezCLfjLNeYWWW4FLF0zNKobIk+j0mCvtC+ytp6eG3MYTGbe32yxnD/1YD06NvDkqR+OsCM6kf/9dJTFTzyAfRk8Cbdj9bGrzFoVgVmCDvU9aOrvirtGhZtGhZtGjZtGhbtGjZtCj++e11CdXmV5YoOH0AxdAk73dimkW3+8zZ4921oFoCIsXbqUMWPGYG9vb7P/Zstdy5YtUavV/O9//2PBggWVIjyrC5EFLBCUke+//55evXoVEn9gEYBHjhzhxIkTdO/enVWrVrFu3TpatWrFQw89xKFDh6xj582bx6VLl2jQoIG1dl2TJk346quv+PLLLwkNDeXQoUOFslu///570tLSaN26NU8++STTpk3Dx8enTOdQv359jh07Ro8ePXjxxRdp3rw5ffv2ZdeuXXz55ZeAJXZv4cKFfPDBBzRv3pwVK1awYMGCsl4uevbsSaNGjejatSsjRozgkUceKfHLujTH7tSpE8888wwjRozA29u7yKw7mUzGX3/9hbu7O127dqVXr17Ur1+f3377rcznIah6TGYzBtMNFzAUxAIqkYCUbD1myUy2PpvknGSuZFwhOjma8PhwTiae5HzaeeK0cWToMqziz05hh5u9GwHOATT0aEgLnxa08mtFsFcwga6BeGm80Kg0JRZWBvj1cCwXkrLxcFTzTPcGdGnkzdLxbbFXydkZk8TTPx21WjDLy8qDV3gxX/yNaBPIiqc68PagpjzfsxFPdgxiUGgAXRp501wRS+1V/SziT6aAnm/DmD/vefEHFit+RkaG9e+1116r8Jx79uwhJiaGp556qsSx7du3x2g0cunSJcASR3hzaSnAul0QN3i7MWVNAqxMZFJZa1/c5Vy9epXAwEAuXrxoU1tNcOfJysrizJkzNGnSpNJjugRlx2w2k5mZiYuLS7HWOUHVc7++Fjl6I+cStSgVcpr6u2A0Gckx5pCeoyM9WwWYMcgvIVE4PlOGzGrNc1A6WK17SnnFHF05OTlERUVRO6gBA78+TLJWz9xHmjGuU5B1zL7zyUxafoRcg4kujbxY8mQbHNRltwQu23uRuX9HAjCuY11mD2qGXH5L4oskwdFlsOlVMOnAOQCGLYW6HUucPzU1la/+PYeji1ux47Iz03muR0M8PO5cBnNpuHTpEvXq1SM2NpbatWuX+fnFtcgcP348p06d4siRIyXOs2LFCsaOHUtycjLu7u58/fXXvPHGGyQkJFjjiV9//XVWr15tjbUeMWIEOTk5/P3339Z5OnXqRMuWLUUSiEAgENyPGExm5DIZiltv9PcRkiShM+lIzckFZJglHScSTti4cFXURYYKmeSMQpFtFXkFQu92LtzKYtXRayRr9dTzcmR0+zo2j3Vq4MWyCW2ZuPwwe84mM+mHw3w/rm2ZRODXO8/zQb57+X9d6/Nq/5DCWc95mfD3C3B6tWW7UR8Yshgcy14w+n5Bq9Vy7tw56/bFixcJDw/Hw8ODOnUsr2NmZiarVq3ik08+KfT8/fv3c/DgQXr06IGzszP79+9nxowZPPHEE7i7uwMwevRo5s6dy6RJk3jllVc4deoUixYt4v/+7/+s87zwwgt069aNTz75hIEDB/Lrr79y5MgRlixZUsVX4PYIASgQCATVhN5o5mxCFvZqBQ28q69Ab0q2joQMHUFemipPwjJLZmtSxs0lV8ySGYXkiQJ3DFIOpptcuBqVBsyQnQcahS/Bvs5VVhKm6DXDn8evAfBKv2BUisJCs0N9T36Y2I7xSw+x73wKE5YfYun4tiVeT0mS+L9/zvLZ9rMAvNCzEdN7NSp8ftfD4Y8JkHoB5EroORs6ToX7yEJcHo4cOUKPHj2s2wXxfOPGjbN2b/r111+RJIlRo0YVer6dnR2//vorc+bMQafTUa9ePWbMmGETF+jq6srWrVuZMmUKDzzwAF5eXrz99tvWEjBgsfatXLmSN998k9dff51GjRqxdu3aaqsBCEIACgQCQbWRmWfAJElk64yYzFK1WQHTsw0YzWZStHo0HpV3WzCYDDYiL9eQS64xt8ixMmQoZQ5IErjbO+Lp5IFGpUGRX8bEZDYTFZeF3mhGqzPibK8qcp6qINdkEett6rrTt9ntY7baBnnw46R2jFt6mAMXUhm/7DDLxrfF0a7oaypJEu9viuab3RcAeLlfMM91b3jrIDj0LWx9A0x6cA20uHwD21Xa+d3LdO/evcTap08//bSNWLuZ1q1bc+DAgRKP07JlS/bs2VPsmOHDhzN8+PAS57pTCAEoEAgE1URWntH6b53RVC0lkCRJIs9oSVzIzDNgliTkZbSuFbhwby25YjAbihyvlCttYvU0Kg12SjvOJGjRm814ObriZGcr8BRyOR6OapK1OlK0+jsmAPVGM3qT5Xq8NqBJiZbHB+rmi8DvD3HoYirjlx1i2YR2ON0iAs1miTl/n+bH/Zbi0rMHNWVCZ9tSIuSmw7qpEJUfNxY8AAZ/CZqaFZsnuDsRAlAgEAiqAbNZQqu7IQDzDNUjAA0mCVN+rTmT2WKNLE5cmc1mq1XvVhduURS4cG8uuaKSqwoJKbNZwlBQAuY2pVQ88wVgZp4BncF023GVSbJWhwQ82NCLB+q6l+o5reu489NT7Xny+4McvpTGuKWHWD6hrfW6mswSr68+yW9HYpHJ4N0hLQrFFXL1KPwxHtKvgFwFfeZD+2fgDrq+Bfc2QgAKBAJBNaDVGW1cU3mG6uk8cmvZkoxcg1WoGEwGi0XPmGNTSLkoZDIZGuUNkVfwb0UpO1HojGYkQCGXobyNK9xOpcDZXkVWnoGUbD0BbmXvtlMWsvIMZOtNyICJneqW6bmtAt1Y8VR7nvjuIEcvpzF26SF+mNgOjUrBrFURrA2/jlwGHw8P5dHWN2W0ShIc+Aq2zQazAdzqwvBlUKtwu0SBoCIIASgQCATVQFa+9U8pl2M0m8mtYP248lLg/lXKZRjNEuk5OnLM18gthQv3ZjeuvdK+QokZuvx12CsVxc7j5aQmK89AWrYeXxf7KoublCSJ+AyL2LVTSAS42ZfwjMK0rO3GyskdGPPdQY5fSefJ7w/h72LP5tPxKOUyFo0MY2BL/xtPyEmFv6ZAzEbLdpNH4JHPwcGtEs5IILBFCECBQCC4w0iSRFaeRVx5OqlJyMwjz2CyaQFYVZjMJvKMeVaLXlauGnBAJ6WgwA2zJCcrT4cks6zvZhdugRu3KBduRSmwgNqpis9qdbJTYqdUoDOaSMvR4+VUNZ0Y0nMM5BpMyOUyHCpwp2xey9ViCfz+IBGx6UQAaoWcr8a0plfTm1qDxR6CVRMg8yoo1ND3PWj7lHD5CqoMIQAFAoHgDqMzmtEbzchkMjwd1SRm6jCZJYwmCZWy8m74BpOhUKzerS5clbkOMgCZHrlch9nkgJvaH19XOxyUpXfhVpQCC2BJ/XRlMhmeTmqup+eSotXj6aiudDFqNkvEZ1quk4dGTUW7tTav5crKpzrwxPcHydEbWfJkG7o29i44GOz7DLbPA8kEHvVh+HLwD63gUQWC4hEFhASCGsacOXPw9fVFJpOxdu3a6l5Omdm5cycymYz09HQAli9fjpubm/XxOXPm0KpVqzu6pu7duzN9+vQ7esziKMj+dVQrUCrkVqtXrrF8bmBJksgz5JGam8rVzKucSTlDRHwEEQkRnE09y9XMq6TmplrFn1KuxMXOBV9HP+SoAWjq04hANy8ADEYVjirHOyb+AHT5FkD7EiyAAO4aNQqZDJ3RZHWlVybJWh0Gkxm1Qo6bQ+VkGzcNcGH3yz3Y92rPG+IvOwVWPg7/zLaIv+aPwdO7hPgT3BGEABQIysH48eORyWTIZDLUajUNGzZk3rx5GI0VuxlFRUUxd+5cvvnmG+Li4ujfv3+F11oWwZWZmcmbb75JSEgI9vb2+Pn50atXL1avXl1iLa3bMWLECM6cOVOu55aVW8VnAatXr2b+/Pl3ZA2locD9W5BsYZ9v9SpNH1mT2YRWryUxO5HL6ZeJSoriePxxTiWd4kLaBeK18WTqMq3xe/ZKe9zt3anlXItGHo0I9Q2llV8rGns2xkvjb0m8kMlQK+Q42ymRy2ToTeYK97QtC2ZJQndLD+DiUMhluDtahGuKVl/C6LJhNJlJytIB4OtqX6keWCc7JR756+byPlj8IJzbBkp7GLQIHvse7F0q74ACQTEIF7BAUE769evHsmXL0Ol0bNy4kSlTpqBSqcrVmNxkMiGTyTh//jwAgwcPvqOdDgDS09Pp27cvWq2Wd955h7Zt26JUKtm1axcvv/wyDz30kI0lr7Q4ODjg4FCxbE29Xo9arS7382tST1OTWSJbbxFXzvaWr2B7tRxyC2cCG81GcvU3FVI25t42C1cukxdqj1aSC1eXL/LsVYr8HzSWNWXkGsjINeJwh8rS6I1mpPz6g0V12SgKTydLSZisPAN5BhP2lVQSJiFLh0mScFApcHNQkZtbyRZGsxn++wT+fQ8kM3g2srh8/aqvI4Tg/kRYAAWCcmJnZ4efnx9169bl2WefpVevXqxbtw4AnU7HrFmzqFWrFo6OjrRv356dO3dan1vgFl23bh1NmzbFzs6OiRMnMmjQIADkcrmNAPzuu+9o0qQJ9vb2hISE8NVXX9ms5erVq4waNQoPDw8cHR1p06YNBw8eZPny5cydO5eIiAirxbKg/dGtvPHGG8TGxrJ//37GjRtH06ZNady4MZMnTyY8PBwnJ0ursp9++ok2bdrg7OyMn58fo0ePJjEx8bbX6VYXcAHffPMNgYGBaDQaHn/8cTIyMqyPjR8/niFDhvDuu+8SEBBAcHBwice+dOmSteWTu7s7MpmM8ePHA4VdwGlpaYwdOxZ3d3c0Gg39+/fn7Nmzhda8ZcsWmjRpgpOTE/369SMuLu6251lasvPLv6iVcqu1q8ACmK3TczXzKufSznEx9yInEk9wNvUs17KukZaXZhV/KrkKFzsX/Jz8qO9en+bezQnzC6OJdxPqutXF29EbJ7VTiS7cXKsAvHErcMl3eWbmFp0BXBXojDesf6X94WOnVOCSb0FNya4cK6DOYCI136Lo71qxrOYi0SbCz4/Cjncs4q/lSHh6pxB/gmpBWAAFNQtJAkNO9RxbpalQxp2DgwMpKSkATJ06lcjISH799VcCAgJYs2YN/fr14+TJkzRq1AiAnJwcPvjgA7777js8PT3x9/ene/fuTJgwwUZorFixgrfffpsvvviCsLAwjh8/zuTJk3F0dGTcuHFotVq6detGrVq1WLduHX5+fhw7dgyz2cyIESM4deoUmzdv5p9//gEsfStvxWw289tvvzFs2DACAgIKPV4g/gAMBgPz588nODiYxMREZs6cyfjx49m4cWOpr9W5c+f4/fff+fvvv8nMzGTSpEk899xzrFixwjpm+/btuLi4sG3btlIdOzAwkD///JPHHnuMmJgYXFxcbmt5HD9+PGfPnmXdunW4uLjwyiuvMGDAACIjI1GpVNbX5+OPP+ann35CLpfzxBNPMGvWLJs1lofMfPevUmHkSsaV/O4ZepTUxWCCeG0CcMPdbq+0L9Q1Q6WonLi0PGvc3Q2h6GyvRCaTkWc0VaplrThutkSWBS8nNZn5JWH8XOxQVLAvbnxmHhISzvYqnCq708iFXbB6MmgTQOkAAz+GVmNElq+g2hACUFCzMOTAe4UFyB3h9eugdizz0yRJYvv27WzZsoXnn3+eK1eusGzZMq5cuWIVU7NmzWLz5s0sW7aM9957D7CIma+++orQ0BsB3wWWMj+/G/1GZ8+ezSeffMKjjz4KQL169YiMjOSbb75h3LhxrFy5kqSkJA4fPmx1dTZseKOfqJOTE0ql0mbOW0lOTiYtLY3GjRuXeL4TJ060/rt+/fp89tlntG3bFq1WayMUiyMvL48ff/yRWrVqAfD5558zcOBAPvnkE+s6HR0d+e6772xcvyUdu+D8fXx8buuuLhB+e/fupVOnToBFZAcGBrJ6zRp6DhiMyWzGYDCwePFiGjRoAFhE/bx580p1fmB5XxjMBpvWaDmGXMwGP2QoydQnYDZk3/QMMyDHw94XJzs15jwzXm5eKBVV9zWdV4TwUsrlONkpycozkJlnuCMCMM9Y+vi/m3G0U2KvUpBnMJGabcDbufwlYbJ1RjJyDciwWP8qDbMJdn0Iuz4AJPAOgeE/gE9I5R1DICgHQgAKBOVk/fr1ODk5YTAYMJvNjB49mjlz5rBz505MJlMhMaXT6fD09LRuq9VqWrZsWewxsrOzOX/+PJMmTWLy5MnW/Uaj0WrJCw8PJywsrEJxbmVJ8Dh69Chz5swhIiKCtLQ0zGbLzfvKlSs0bdq0VHPUqVPHKv4AOnbsiNlsJiYmxioAW7RoUSjurzKOHRUVhVKppH379tZ9np6eBAcHczTiFE069SEt24BGo7GKPwB/f//burot/XTzCpVcMZpt48dkkhoVSkDCyV6Fo8rf0jlDqeFaupFsnRF3Ox9cHZRkGjKRy6ouSsdoNmMwFV17z8U+XwDmGvBxrkQxdBsKLIBlbe1WUEbnWnouKdk6vJzKVxImV2/kSqrF8+DuqK480ZsVD38+BZf2WLbDnoD+H4FaUznzCwQVQAhAQc1CpbFY4qqIrDwDdko56qJqjanK9qXco0cPvv76a9RqNQEBASiVlo+TVqtFoVBw9OhRFArb49xsIXNwcCjxZqXVagH49ttvbQQLYJ27ogkWAN7e3ri5uZWYrZudnU3fvn3p27cvK1aswNvbmytXrtC3b1/0+srNxnR0tLXG3oljF1jE8gwmqyu4AJlMhiRJmMwmG5FX0CrtdiK6wIWrUWkwGBxIy5ZwslNR37OhzTgHVS7ZOiN5RhOud+CruaDsilohR3mL69TFQcW19Fxy9Cb0RjPqMlrmyoIkSdYYQPtyHMddoyY+Mw+90UxWntEaw1haMnL0xKblYpYk7JQKfF0qSfCe3wGrn4bsJFA5wsP/B6EjKmdugaASEAJQULOQycrlhi0N2jwDFzMNqBXQ2FeDvIItpBwdHW1crQWEhYVhMplITEykS5cuFTqGr68vAQEBXLhwgTFjxhQ5pmXLlnz33XekpqYWaQVUq9WYTMWX9JDL5YwYMYKff/6Zd955h9q1a9s8rtVqsbe3Jzo6mpSUFN5//30CAwMBOHLkSJnP68qVK1y/ft3qIj9w4AByudya7FEUpTl2gcWwuPNt0qQJRqORgwcPWl3AKSkpxMTE8MQz0wFLBJ4E6E16q8iLz7KUAz4ef7zIeeUyeaFYPQelA/KbxNWFJC1gtCYv3ExBIkau/s6UXynK/VuASiHHUa0kW28kM89QZd02AAwmM+b8DijlEZpyuQwPRzVJWTqStbpSC0BJkkjM0pGQX/DZ2V5FoIdDITFcZkxG2LkA9nwCSODb3JLl69WoYvMKBJWMyAIW3Dck52f36U1mUnMq11p1M40bN2bMmDGMHTuW1atXc/HiRQ4dOsSCBQvYsGFDmeebO3cuCxYs4LPPPuPMmTOcPHmSZcuWsXDhQgBGjRqFn58fQ4YMYe/evVy4cIE///yT/fv3AxAUFMTFixcJDw8nOTkZnU5X5HHeeecdatWqRceOHfnxxx+JjIzk7NmzLF26lLCwMLRaLXXq1EGtVvP5559z4cIF1q1bV676evb29owbN46IiAj27NnDtGnTePzxx4uNUwwMDCzx2HXr1kUmk7F+/XqSkpKsFtSbadSoEYMHD2by5Mn8999/RERE8MQTT+DrH0D3PgMo+FkgSRInEk5wLvUc17KuoTXcmEslV+Fq54q/k78lC9fHkoUb4hVizcJ1VDvaiL+iyr/YXJN8IVYQD1fV5FndrkXfBgqEVEYVZwNbW8CVIQP4Vjwd1cgArc5YqvqFZrPEldQcq/jzcrIjyFNTcfGXcQ1+GAR7PgYkeGACPPWPEH+CGokQgIL7Aot76MaNrKD1VlWxbNkyxo4dy4svvkhwcDBDhgzh8OHD1KlTp8xzPfXUU3z33XcsW7aMFi1a0K1bN5YvX069evUAi9Vr69at+Pj4MGDAAFq0aMH7779vdRE/9thj9OvXjx49euDt7c0vv/xS5HE8PDzYunUrY8aM4Z133iEsLIwuXbrwyy+/8NFHH+Hq6oq3tzfLly9n1apVNG3alPfff5+PP/4YgKSsPJK1RYvLW2nYsCGPPvooAwYMoE+fPrRs2bJQaZubMZrNpJrs+fDzxUUeu4BatWoxd+5cXn31VXx9fZk6dWqhuUxmE58t/oxmoc0YMHAAHTp2ICMvg0XLf0SlUmGUpWBJyAC5ZKml5+HggaeDJX4z1DeUUL9QGnk2opZLLTwcPLBXllwyRHtT+ZeiLF0FLdCMJnOVvjcLyM0XXg63iXdzzW+Am6MzYjRVnSjVlTMB5GbUSoVVsJb0HtQbzZxP0loSPmQyartrCHArORyjRM5stRR2vrIP1M4wbCkM+hRUFQ/REAiqAplU3vL+dylXr14lMDCQixcvEhQUVN3Lua/JysrizJkzNGnSBI2maoOi4zPySMzKw1GtxGC29GH1c7W/IwHudwtms5nMzExcXFxsLFelIS1bT2xaDjKgib8LylIW8y0tmbkGLqVYMmYD3TXWLhDFIUmSpReu8aZYPUMOOlNRAkGB2mwR1C6OWRiNjuTo5LhpVNTxqJyQhKtpOaRm6/F0sqOWW9GiICY+C53RRD1PR0y67HK9FqVBkiQir2dikiQa+zrfNunhbEIWuQYTtd0d8HCsGjfw1dQcUnP0+LrYVyj+TqszciFJi1wmI8TPucj3YI7OyKXUHIwmM0q5nLqeGhztio+EysnJISoqisaNG+Ps7Fx4gMlg6eO77zPLtn8oDFsGng0Kj61mUlNT+erfczi6uBU7Ljszned6NKxRBdTBUuuzXr16xMbGFgpTEZQdEQMouOcxSxKp+YViPZ3USEBsag5JWTo8HdUVrh12v2OWJKsrTQKydEbcNeXv2lEUN7v14jLzcHFQobgphtMsmckz5tmUXMk15hbKwi1ArVDbxOrpDWoSMg04qBUEuQeSrTNyPklLZq4Rk9lc4feIJEnW/r/OxQgOe5UcndFEntFEJVehs8FgMmMqRdydq4OKXIOJjFxjlQnA8paAuRVHtcJaEiYtR4/3LT/u0nL0XE3LRZIk7FUKgjw1RSeDlYX0WPhjIlw9ZNlu9zT0eQeUVRczKRBUFkIACu55MnMNGM1mlAo5Lg4qZECSUkGe0USSVo9fZWX93SVI+Tf+yiI1W4/+JhdhVm7lC8DcmwSg0WTmWnoWdupcazZuriEXiaKdGQVCz0GVL/iUmkK19S5mW6yLrvnJGRq1AjulAp3RRHquAc8Kih+d0VJyRS6T4VSsAFSQkWsgz2DmNqF5lcLNcXfyYt4LLg4q4jPz0OoqRwjfiiUDuHwlYG5FJpPh5WTH1bQcUrR6vJzsrJnb8Zl51v6+LvYqAj00Nj8gykX0Rlj7LOSlg50rDP4cmg6u2JwCwR1ECEDBPU9BmygPR7X1ZufrYsfl1BxSsnR4Oaor3WVZU8nMNXAlNQcfZzt8KkH4mswSiZmWG6u7Rk1ajp4snaFSRKYkSehNenKNuWh1EiADuRbMTqTnmDDkxiPJbsR1KmSKGyIvPwPXQeVQYi09k9mMVmexzhXEkclkMjwcVcRlmEjLrrgALIg/dbRTFpt9bk0EMZioQE3jEikuA/jW9RQI4aw8I26VLOyNZgmTWUJGxS2AAG4OKuIz5OhNZjLzDDjZqYhNzbF2X/FxtsPXpYIt3ox6+Gc2HMiPWQ1oDcOXgXtQhdcvENxJqv2u9+WXXxIUFIS9vT3t27fn0KFDxY7/9NNPCQ4OxsHBgcDAQGbMmEFeXtHN0QWVS1aegRd/j2Dh1hhy9JXcIL2KyDOYyNYZkSHD46abl4uDCgeVApMkkVTKxIV7gaQsHeZ8i0haJfRPTdHqMJotdeJquTmglMtssl1Li1kyk2PIITknmdiMWGKSYwiPD+dk4knOpZ7HZLbcsPUkYSYHkGEv98ffyZ8G7g1o4dOCVn6tCPEKoY5rHbw0XpYs3FIUUs7KsyRn2CkVNoLITaNGhowcfekyS0s6BhSd/XszBaVg8oxmqjI6+0YLuJKvT0EySFVkAxcUgFYrFcVaIkuLpSSMRcQnZuosbvw8S7JHHQ8Nfq4VTPZIuwRL+94Qfx2mwMQtQvwJ7kqq1QL422+/MXPmTBYvXkz79u359NNP6du3LzExMfj4+BQav3LlSl599VWWLl1Kp06dOHPmDOPHj0cmk1lLYtRkJElizfFrNA1wIcTPpbqXU2bm/R3Jn8euAvDnsWu8PagpfZr6lvsLteB5VZmHVGD9c3FQ2sQ6yWQyfF3suZSSbXUXqe5xK6DOYCL7JuF+NT0XlVJerEuyOIwms1U8+7rYI5fLcLZXWayAeYbbzms0G2/E6hkt7tvbuXBlyLBTuGA2g1wGjT0boMCeC0m5mExqXNTuOFewZ2uBsHFxsF2vSiHH2V5p7TXrf5vEjZIwmc03yr+UcK3VCotL1ixJVGU1mNJaAMHyYykxS0dWnhGzWapw/UybdVRS/N/NeDjakZSlt4YNqBSWZA+Nunzv84LvJ/nFnbBhCugywN4NhnwNIQMqadUCwZ2nWgXgwoULmTx5MhMmTABg8eLFbNiwgaVLl/Lqq68WGr9v3z46d+7M6NGjAUt9s1GjRnHw4ME7uu7ysjMmiZm/R+DqoGLjC11umwlYE9l6Op5VR68ik4G/iz3X0nP5309HeSjEh7mPNCPQo+xZvEqlErPZTE5OTqGuD5WBySyRfpP791ac7ZVo1Epy9EYSs3R31etRHtLyax862SlRyGVk5Bq4nJJNQ2+ncsVfJWstpXTsVQrc8l2nzvZK0nL0ZOYa8XPJd+Hmd8ooSM7Qm4q2PCpkCttYPZUGe6U9aTkGrqXlolErcbGzdFLxdDKRrNURl56Ho6+y3NYjs/lGcoZrEQWEPRzVFgGYY8DX1b5cx9HqTFYLY0nXWSaTYa9SkKM3oq8iAWi26bxR8uvuoFKgUsgxmCyu8rJ22igOXQm1CMuDWinHVaMiPUePg0pBkKcjqgoITINBj8qQiXrLFNBnQO12lhIvboGVtmaBoDqoNgGo1+s5evQor732mnWfXC6nV69e1gK2t9KpUyd+/vlnDh06RLt27bhw4QIbN27kySefvO1xdDqdTeHbrKwsAAwGAwZD1RY4vZV14RbrWUaugRd+OcZPE9rcFbFnKVodr64+AcDkB4OY2r0BX++6wHd7L7EjOpG955J5rlt9Jj0YVKZf8mazmaysLJKSkgDQaDSVmpyQkWvEaNChVshRmA3k5BR+vd3tJLJz9KRkGHBWmFEqKu/4NY2UjBwksxknjRxHOyW5eSZ0ehMX4g3UdndALrN8LnNzc0t8HYxmicR0S/szd0d7cnJz0Bl15Bp0SEYFeUYIj72IiaLFnkquwk5hh4PKATulHQ4KB1SKW4SFAfIMeWi1OiSjAaXaUpIDwFklkWo2kJunJz7VbBWgZSVbb8Rk0FkKABv15Bht16sA5GYjBqOZlHRKLBlSFGmZlvXbq1TW9ReH0mxAMhrIg1K9FmVFZzRjNuqQy2UY9XkYSxEJoJGbSNcZSMmQUEqVF5yYnZuLZDQhM8nJyak8T4CnHTjI5WhUCgz6PAzljHYwG3UkXTmLa9x/KPWZmDo+j7nb66BQwR2+f1QGBoMBSTJhNhcf0iBJpmq5R5ZETVvP3U61CcDk5GRMJhO+vr42+319fYmOji7yOaNHjyY5OZkHH3wQSZIwGo0888wzvP7667c9zoIFC5g7d26h/bt37yYyMrJiJ1EGjGbYfFIByJDLJI5cTmf6d1sZEHhnqv6XF0mCpWfkpGbL8ddIBOvP8e8/5wgBXmoBqy7IOZsJ/7f9HCv2nmVYfTPBrmX/Is/Ozq70emeZehlGCTRKiZzE24/LMoDBLCM9XsLxHk2LMpghyyBDLgNjiuX1MUuWfSYJEq5ZRFVpkJDINkjozQpkMiOJ8ZmYpBuuZbnkhgw1ZlkWErkoZcobf3LL/435/2WTXeLxsgwyDGbIUUok3WSw0pkg2ygjWQauaonyyKRsI+hMMuwVEnlJRY/JNUKuyfL+cCqHzkzXyzBLkKuSSC7FW7zgvNLlEukJZT9eSehNoDXKUMlBn1S619xohkyD5VqnqitPqBVcm7xkCWUN++2lMOtQG7NQ5KbgefZ3DtSfSWJeKGzZVt1LKzdZWVmcvybH3rGIeoY3kZedxba880XXPaxGkpOTq3sJ9xR31e1u586dvPfee3z11Ve0b9+ec+fO8cILLzB//nzeeuutIp/z2muvMXPmTOv2tWvXaNq0KV27dr2jhaB3nkki9+BxfJzteKVvY1784yRbr8l5sk872terWcU2b2bN8eucOHAKlULG4vEdaOpvG7s4XpL4+0Q8CzbHkKjV81Wkgodb+PFa/2B8SkhjNBgMbNu2jQ4dOiCXyzEajZUWD3j6eiZv/nEStVLOyklti41zi4rLYsaqE8jlMr59IuyedAUv2HSGXWcTeaSlP891r2/dfyklm5mrTpGjN9Ij2IsO9gl07twJpVKJJElc014jJjmGmJQYolOiOZNyhoRMHT76OchQkqRaiF5+BgAXOxeCPYPRGB7i3NV6BPup+HhYO1Ty8rsMJUli2JJDZOuMfD26FfW8boQKmCWJKb9EcDE5m4Et/Hi+R9kK75rMEqO+O0RmnpH3H21G49puRY6LTctl8k/HkMng5wlt8XQqfSbsxeRs3l4Zjlop54+n25eq1+2pa5nM+fMkLiqJlZM7oFRW7tf0d/9d4o9j1xjU0p8pN70XisMsWa5VRq6RBUObERboVuF1ZOYZmLbEkvS35pkOOKgrWJOvsjDqkO/7FEXUWjCbUHgGsaPeTLoMHIFKVZXVGaue1NRULu65gMbZrdhxOVnp9O5Sv0YWghZUHtUmAL28vFAoFCQk2P7ETUhIuG0/0Lfeeosnn3ySp556CoAWLVqQnZ3N008/zRtvvFGkBcnOzg47uxtCJDMzEwCVSnVHP8xbIy3mhX7N/XisTR0OXkrj9yNXefGPk2x6oWuRMWrVzfX0XOZvsFhjp/dqTGgdzyLHPdamDr2a+bNwaww/HbjM+pPx7DqTzIt9GvNkx6AS621VxWvxy/FzXMsy8Xgbf/y93Isd287ZmeBa19gRncjXe6+xaGRYpa6lusnIMfDHiUT0RjMDWwfZ/Kpv4ezMW4MVTFh+mJ+PJHDY8yxbZJs5kXSCiPgIMnQZhebz1M/AaJLh7HyFJ9o/SKjvFFr5taKOax1kMhnnk7T0/GQXSTkSanuXcieZgKVg95lkHSqFjJBAn0IC6vneTRmx5ADf7b/GkDb1aRpQ+uSq/edTiErS4aZR0bFxrduGYzR1dsbPw4Wjl9PYFJPOs91LLzT3Hk3kWpaJHsEeeLq7luo5Tevacy3LxDXArLDD2blyu+SEx+VyLctEoI9bmSw8Lev68OvhWLadyaBr04rHv0WnpHIty0QtNwd8PN0qPF+lkHwWVo2HhFOADLq8iOHBWeRt3nrH7xlVgUqlQiZTIJeXFIuqqJHnW9PWc7dTbQFoarWaBx54gO3bt1v3mc1mtm/fTseOHYt8Tk5OTiGRV9DvtCZ3tDOYzGyNtAjd/s39AZjzSDMaeDuSkKnjpVURNW79ZrPES39EkKUzElbHjf91Ld5S4OqgYu7g5vw15UFCa7uSpTMy5+9IHvniP8Jj0+/MovNJ1urYdDIegCc7BJXqOTN7NwZgXcR1YuKzqmpp1cK6iGvojWZC/JxpFuBCSk4KOy7uYOH+hYxdM5ap23uSrPwSgJiURiw9cILdl3eToctAJVcR5hfG+FbjWdRvESse2YGzqScAP499nLe7vc3gkMHUdatrjVWr7+VIkKcGvcnMf2cr5rKJzn8tGvo4F2k9a1/fk4Et/TFLMPfv02X6HG05bXmP9AzxLTEWd0Qbi+BZdSS2TMfYGWOJPegRUriqwe1wdVAR4Gqp0RiToC3180pLwfu7rJUI+jaz/DDfGhmPuRJ6FZ9LtJxbAx+nCs9VKUT8Bt90s4g/R294cjX0fAvkd5WjTCAoNdWagTBz5ky+/fZbfvjhB6Kionj22WfJzs62ZgWPHTvWJklk0KBBfP311/z6669cvHiRbdu28dZbbzFo0CCrEKyJ7D+fQkauAS8nNe3y3b0atZLPR7VGrZSzPTqRZXsvVe8ib+HH/ZfYey4FB5WChY+3KnWySovarqx+rjPvDGmOi72S09czGfrVXqasPMZ/Z5Mr5cZREr8fiUVvMhMa6EaL2qWzujSv5cqAFn5IEnyyNaaKV3hnMEtmzqeeZ8l/JwHIkG+m7qd18frIi54/9uTFrS/y04mfOJl4kkzFRnR2GwHwNc5iXucVRDwTgfZ1Lcf+d4xlg5cxrf00dp50RgL6NfMj9DZuQJlMZhU8O6IrFsQWFWex2Dfxv72l6rX+Idgp5Ry8mMqmU/GlmleSJLbl/yjr28y3hNEwoKU/GrWCC8nZHLmcVqpjZOYZOJo/tnvj0gtAgGA/iyiKSajcHyPpOXri89v2BfuVLb6rU0NPnOyUJGTqCL+aXuG1nM0Xt42qWwDqc2DtFFjzNBiyIagLPPMfNHioetclEFQx1frTZsSIESQlJfH2228THx9Pq1at2Lx5szUx5MqVKzYWvzfffBOZTMabb77JtWvX8Pb2ZtCgQbz77rvVdQqlYtOpOMDyC/pmd2jTABfeHNiEt/86zYJNUbSr50HzWqUTLFXJ+SQtCzZZXL+vDwixibsqDQq5jCc61KVvMz8WbIpi9bFrbDgRx4YTcdR2d+DxNoEMe6A23lWQcWEyS6w4cAWAJ9rXKdNzZ/ZuzOZT8WyNTODE1XRa3iYmrCaSZ8zjdOJpwuPDLX8J4UTER5CX50GA7kskjBxK/RKzzCKo6rvXp5VfK1r5trL8368VXnY+PL5oKyfT5KzZ783YsAaoFTdCE8Jj09kamYBcBi/2aVzsenqG+LJs7yV2RCdVqHZcgQC8Nfb0Zmq7a3imWwMWbT/LuxuieCjEp8T6dqeuZXItPRcHlYKujb1LXIeTnZKBLfxZdfQqvx+OpW1QybFRe88mYzRL1Pd2pI5n2dy4Ib7O/BuTTHR85VoACyyqtd0dyuyat1MqeCjEh3UR19lyKp7WdYoPrSiJc0mWc2tYnQIwMcri8k2KBmTQ/VXo+hKU4CIVCO4Fqt22PXXqVKZOnVrkYzt37rTZViqVzJ49m9mzZ9+BlVUORpOZLactloYBLfwLPf5kh7r8dzaZrZEJPP/Lcf5+/sEKxUyBxX17LklLfS/HMpeZMZrMzPw9Ap3RTJdGXjzRoW651+HtbMfCx1sxsXM9fjscy9rwa1xNy2XhtjP83z9n6NLQkwYyGb2MZiortGNnTCLX0nNxdVAxKDSgTM9t6OPMkFa1WH38Gh9vPcOPE9tVzqIqmeScZCLiI6xCLzw+nKikKExS4dIOnuZRAPh4JDCr2zu08mtFS9+WuNoX/qFhMBh4spGZH6+6cep6JhOWH2bNs51x1VhenI+2WH4UDA2rTSPf4q1H7ep54KhWkKzVcep6RrnFdIEALMld+Uy3Bqw6Esu19Fy+2XWBF3o1KnZ8gfu3W2PvUhVDBhjRNpBVR6+y4WQcsx9pVuLndGeMJe63rNY/uGGdq2wLYHndvwX0a+7HuojrbD4dz6v9QypUouZc/rlViwVQkiB8BWyYBcZccPKFx76Del3v/FoEgmqi2gXgvc7Bi6mkZutx16iKzPaVyWR8OKwlpxbtsWQM/nWKhY+3KvfxouIyeWvtKY5cTiO0tiufjQqjrmfpLXhf7zxPRGw6zvZKPhzWslJqkDWv5UrzWq68PqAJm0/H8dvhWA5cSGX32RR2o+Cvj3fxaFhtRrQNLFFYlMTPBy4D8Hib2qW+sd/MC70asS7iOrvPJHHoYqrVZV8dmCUzF9IuEB5vseYViL2rmVeLHO/p4Gm15rXya0Vz71AmfhdHqsHAgocH06tpya5OOwV880QYw785yIWkbJ75+Sg/TGzH4Uup7D2XgkohY3oJ4gosxXi7NvZm06l4tkcllksAZuuMXE611M0rzgUM4KBW8NqAJjz/y3G+3nWO4W1qE1BMNneBAOzbvORrUsADdd2p7+XIheRsNpy4zoi2t7cwS5LEzjOW+L/uwSVbGG8l2Nciis4kaCu1+0Z0fIGgLt/nrFtjb9RKOZdTcohJyCq3kNTqjFzPsLii77gFUKeFDS/CiV8t2/V7wKNLwKnsQl0guJsRArCK2Xjyhvv3dtY4N42aT0eGMXLJflYfu8aDDb14tHXtMh1HqzPyf9vOsHzfJUz5cXYRVzMY+Nl/vDu0OYNb1SpxjlPXMli0/SwA8wc3x9+1csuhOKgVDA2rzdCw2lxKzubXQ5dZuf8CqdkGvvvvIt/9d5HWddx4tX+TcgmvKyk57DxjsbqMaV8+y2VdT0eGtwnkl0NX+HhrDL893aHSC/EWRa4hl9NJN7lw48OJSIhAqy/aBdjQoyGhvqE2gq+Wcy2btW45HU9q9hW8nOzKJEJ8nO34fnxbhi/ez/4LKbyx5iRn8gP2x7SvW+quLw+F+LDpVDw7ohOZ0bt4l3FRxCRkIUmW9Xg6lVx8+OGW/vy0/zKHLqWyYFM0n48qOpv7fJKWs4lalHIZD4WUXgDKZDKGtwnkg83R/H7karECMCoui4RMHQ4qRbney0GeGpQyiRy9idi0nDL9iCuOAhdwWeP/CnC0U9K1kTf/RCWw+VR8uQXg+fz3k5eTHW6aO1gBIf6UxeWbchZkcujxBjw4Eyq5BqlAcDcgBGAVYjJLVktD/yLcvzfTrp4H03s1ZuG2M7y59hStAt2o713yL2NJkthwMo756yNJyLR0POnf3I+nutTng03RHLqUygu/hrPnbDJzH2l2204GeQYTM34Lx2iWGNDCj8GtyuY+LStBXo682LsRjfVncWzYlj+OXWdHdCLHrqQz+tsDzBvcnNFljOFbcegykgRdGnkRVMa4xZuZ1rMhfx67yqGLqfx3LpkujcpuwSmOpOwkm1i98PhwYpJjinTh2insaOHbwiZWr4VvC1zsSr7xrjpisRQ+1vr2JU5uRxN/Fz4fHcak5YdZddQyj4NKwZQeDUs9R/dgi0Xl5LUMEjLz8HWxL9MarO7fYuL/bkYmk/H2oKYM+uI//o64zpMd6hYpvgo+kx0beBbZ/q04Hmtdi4+3xnD0chrnErNo6FO0kPo3P/u3UwPPclmilQo5fhq4mm0Rk5UhAM1miTNWF3D5Le39mvtZBeD0XmUX9nAjA7ihT+W3gCwSSYKjy2Hzq2DMA+cAGPY91O10Z44vENRAhACsQg5fSiVZq8fVQUWnBkXX0LuZKT0asu98MgcupPL8L8dZ/Vwn7Irp1XkhScvsdafZk19qo66nhjmPNKNH/o135eT2fLbjHF/sOMsfR69y7HIan48Oo1lA4fivhdvOcDZRi5eTHe8MaXFHrF4AChk8FOxN3+YBJGblMX99FH9HXOf1NSc5k5DFmwOblEq85BlM/H44FrDEVVYEf1cHxrSvw7K9l/h4SwwPNvQq1/UwS2bOpZ4r5MK9nnW9yPFeGq9CiRnBXsEoy1GGIilLZxUhw9uUzZpcQI9gS5/nt/46DcDEB4PwLqG49814O9sRGuhGRGw6/0YnMrJd2QR9aTKAb6V5LVdGtg3kl0OxzP37NOumPlioDmVBTG5BWZOy4ONiT49gb/6JSmTVkau8NqBJkeN2FcT/laH8y60EaCSuZsuIjs+kX/Oyr/VWrqblkq03oVbIy5zYdTO9mvigkMuIjs/iUnJ2uX5sFSSANLqNgK5U8jJh/XQ49adlu2FvGPoNOJb8nSwQ3Mvc13ZvSZLYHpVARhE9YiuDTfnu3z5NfVGVQsQo5DI+HRGGu0bF6euZfLCp6HIkeQYTC7fG0O/TPew5m4xaKWd6r0Zsmd7VKv7AYkWY2bsxKyd3wM/FngvJ2Qz9ch/L9l60qWV28EIK3+65AMD7j7aotqLUPs72fDayFbPyM0yX77vEhOWHS/X6bDoVR1qOgQBXex6qwE23gOe6N8RBpSDiaoa1XEhx5BhyOHTtEEuOLuG5Dc/R6ftOuCxwIfiLYEb8MYL3/nuPjWc3WsVfI49GDG86nHcfepcNozdwbeY1Emclsu3JbXzU5yPGtBxDM59m5RJ/AGuPX8NklmgV6HZbK1VpeLJjEC/3C6ZPU1/+161snTYAelrLwRTTi+82RMdZrFXFZQAXxaw+wTjnlyBadSTW5rH4jDwiYtORySyfy/IwPL8m4J/HrmEwFW7lmJFr4OiVgvIv5bceB2gsn9GC61BRCuL/Gvo4VagHuZtGTYf6FstqgTW1rBSUgKny+L+4CFjSzSL+ZAroPQ9G/y7E333E7t27GTRoEAEBAchkMtauXWvz+Pjx45HJZDZ//fr1sxmTmprKmDFjcHFxwc3NjUmTJqHV2obnnDhxgi5dumBvb09gYCAffvhhobWsWrWKkJAQ7O3tadGiBRs3bqz08y0L97UF8K2/TvHzgSs89WA93ny4aaXObTZL1ppkRWX/3g4/V3s+Hh7KpB+OsHTvRTo39KRnkxs3qh3RCcxed5rY1FzAEpQ995Fmxf4K71Dfk00vdOGlPyL4JyqRuX9HsvdcMh8OC0WtlPPiqggkyVLstjSJAlWJTCZj6kONaOjjzIzfLK7roV/t5btxbYp1if+035L8Mbp9nQrd3ArwdrZjfOcgvt55noXbztCria81ED8xO9EmVi88PpyYlBjMUmExYK+0p4VPC5tYvRY+LXC2qzrLhyRJ/J4vfMpr/buZ57qX3u17Kw+F+LBw2xn+O5dMnsFUaneo2SxZ49WalFEAejrZMb1XY+avj+SjLTH0b+FvdfVujbR8JsMC3fApo0u6gIdCfPByUpOs1fFvdCJ9brEk/nc2GZNZoqGPU6njJYsiIP8jXSDcKkpMJbh/C+jXzI+951LYcjq+XD8MzlstgFUkACUJDn8HW14Hkx5cA2HYUgismZn9gqojOzub0NBQJk6cyKOPPlrkmH79+rFs2TLr9s3dwwDGjBlDXFwc27Ztw2AwMGHCBJ5++mlWrlwJWDqM9enTh169erF48WJOnjzJxIkTcXNz4+mnnwZg3759jBo1igULFvDwww+zcuVKhgwZwrFjx2jevHkVnX3x3NcCsFcTX34+cIXl+y4xun2dUsXclZajV9JIzNLhbK+kU8Oy/drs2cSXCZ2DWLb3ErNWRbDpha4YzWbm/R1p7Sji72rP7EFN6dvMr1TuSXdHNd+ObcMP+y7x3sZo/olKpP+i3TTxd+FqWi613Bx48+Gi3VnVQb/mfgR6dGTyD0e4kJzNkC/38uWY1kXG4526lsGxK+ko5TIeb1vxFlUFPPVgXX7Yd5Ho+Cye+OX/SOcfwuPDidPGFTneW+NNmH+YTXJGY8/G5bbilZeIqxmcTdRip5SXuRROZdMswAVfFzsSMnUcvJhKt1JaxK6m5aLVGcvtrhzbsS4rD17mfFI2n28/a/2BZ83+LYf7twCVQs6jrWuzZPcFfj9ytZAALOj+URHrH0CtfAvg5dQcsnXG28bvlpYCQR1SBpf67ejTzI+3/jrNsSvpZY7vzDOYuJySDVSRBTA3Hf6eBpF/WbaDB8DgL0FTs/raCu4M/fv3p3///sWOsbOzu20L2qioKDZv3szhw4dp06YNAJ9//jkDBgzg448/JiAggBUrVqDX61m6dClqtZpmzZoRHh7OwoULrQJw0aJF9OvXj5deegmA+fPns23bNr744gsWL15ciWdceu5rF3D3YB+6B3tjNEu8tzG6UucuyP7t3cS32Di+2/Fq/xCaBbiQlmNgzHcH6L1wN1sjE1DKZfyva33+mdmNfs39yxSbJpPJGN+5HmundKZ+fhu6nTFJyGTwyeOhONvXrD6LzQJc+WvqgzxQ153MPCPjlx1m+S3ua4AVBy3Wv37N/fBxLp9VJ8eQw8GrB/nmyDc8u/5ZOn7fkTqfeXHd/CMAu045svXMEeKy4pEho7FnYx5v9jjvPfQeG0dv5PrM6yTMSmDLE1v4sPeHjG4xmqbeTe+4+AOsbs9+zf1wqebXVCaTWV3yO6JK3xUkMj/+r5GvU6nCJ25FpZDz9qBmgCWU4FyilvQcPQcupAIVE4AAwx+wWFb/jUkkMSvPut9slqyZ6N2DKxaK4KQCbyc1kgRnKqEeYIElMbicmbs34+tiT+s6bgBsLYMb2Gy2dGAxS+BiryxTTGmpuHYUvulqEX9yFfRdACNXCvF3j5GVlUVmZqb1T6fTVWi+nTt34uPjQ3BwMM8++ywpKSnWx/bv34+bm5tV/AH06tULuVzOwYMHrWO6du2KWn0jfKpv377ExMSQlpZmHdOrVy+b4/bt25f9+/dXaO0V4b4WgABvDmyCQi7jn6gE9p6rWN/SAsxmic2nSpf9ezvslAo+HxWGRq3gfFI2uQYT7YI82DCtC68NaFIha0DTABfWP/8gj+e7B6f2aEiH+jUzJsbb2Y6Vk9vzWOvamMwSc/6O5PU1p9AbLe7WzDwDa49b4upKm/wRr41n87nNvP/f+4z8YyQhX4TgvMCZDt934JkNz7D46GIOXD1AjiEHg/1WZPIcVFJtauuW0cj4N71dd9DL4xfau86nqfNYajt0wlntfccSZ4ojz2BiXYTlegx/oPKsoRWhoNTK9ujEUvfRLRArZXX/3ky3xt70DPHBaJZ4Z0Mk/0QlYjJLBPs6VyhLHKCRrzNhddwwmSVWH7tm3R8Zl0lSlg6NWkHbehXrlAE3yrVEV7A/dZ7BxKUUS03FynABww0RvbkUAjAuI5fPt5+l+8c7ef6X44Dle6jSPjOSBPu/gu/7QvplcKsDk7ZAx+egBnwuBZVL06ZNcXV1tf4tWLCg3HP169ePH3/8ke3bt/PBBx+wa9cu+vfvj8lkqcoQHx+Pj4/tjzmlUomHhwfx8fHWMQUdzAoo2C5pTMHj1cF97QIGS/eHJ9rX4Yf9l5m/PpIN07oUyhosK+FX04nLyMPJTkmXRl7lnqe+txOfjQxjye4LjGwXyNCwWpX2halRK/lwWCizB92+NExNwU6p4OPhLQn2c2LBpmh+OXSFC0lavn7iAdaFXyPXYKKxr1Ohkh8ms4kzKWeISIiwiddLyC7aEuXn5GfNwg31s7hxG3k0YsvpRD7ZGsPllBz0RomY+Gxi4rMLPd/XxY76Xk408HGkvpcT9b0t//d2tsNeJb8jAnHL6Xiy8ozUcnMoVeb5naBzQ0/USjlX03I5l6gtVbHvGxnAFbNWvflwU3afTWJnTJI18aBvJWTUgiVm9viVdH4/Esv/utZHJpNZ3b+dGniVy/J/K8G+Tvx3LsUav1deziVqMZkl3DUqfCrJ6mZp9RjNgQuppOfoC9Xz0xvN/BOVwO9HYtl9JomCNuDOdkoeaRXAM+WIHSySnFT4awrE5AfUNxkEj3wBDm6VM7+gxhEZGUmtWjdq294as1cWRo4caf13ixYtaNmyJQ0aNGDnzp307NmzQuus6dTsO/8dYnqvxqw5fo3o+Cx+PxLLqDKWq7iVguzfnk1K7klaEr2a+lZpYkZNF38FyGQynu7agIY+Tkz7JZyDF1MZ/OV/yLCIquFt/Dhw9YBNfb2TCSfJNeYWmksuk9PYs7FNyZVQv1D8nIoWBgNa+DOghT8Gk5nY1BwuJGVzIVlr+X/+v5O1ehIydSRk6th/IaXQHGqFHFeNCjcHFW4aFa4OKlwd1NZ/3/i/2vL//H0u9qoydYH4I79m32MP1K607hEVRaNW0qmBJztjktgenVhKAZifAFJBa1U9L0cmdq7HN7svcC3d8l7o26xyPk8DW/oz9+9ILiRlc+xKGg/U9bC2f+sRUjm1IwusdQWCuLzcXAC6sn6IBHk5EuLnTHR8Fv9EJTIs3y1+JiGL3w7Hsub4NVKz9dbx7et5MKJtIP2b++OgrqReu7GH4I+JkBELCjX0fQ/aPiWsfvc4zs7OuLhUPJShKOrXr4+Xlxfnzp2jZ8+e+Pn5kZhoW8XAaDSSmppqjRv08/MjIcHWsFCwXdKY28Ue3gnujrt/FePuqGZ6r8bMWx/Jx1tiGNjSv9yxU5IksfFkvvu3efncv4Lb0yPYh2/GNeKFX6KsmdDIdDyzvTVmWU6h8RqVxiYpI9Q3lBa+LdCoyp6dqVLIqe/tlJ8sZCsiMnIMXEjWcj4pmwtJWqswvJSSg95oRm8yk5SlIymrbLEq9b0dWTqubalcltfSc/kvP4yhIEatptAzxIedMUnsiEos0fKTlWfgirUFXMW/5Kc+1JA/j10jWaujtrtDmcvK3A5nexUDWvjz57Gr/HY4lobezhwrKP9Swfi/AoJ9b7iAJUkqt3iLsbaAq9ybZr/mfkTHZ/FXuKUkzm+HYwmPTbc+7uNsx7AHavN4m8AKu91tMJth/+ewfR6YjeBeD4Yvh4BWlXcMwX3J1atXSUlJwd/fcv/u2LEj6enpHD16lAceeACAHTt2YDabad++vXXMG2+8gcFgQJXf2H7btm0EBwfj7u5uHbN9+3amT59uPda2bdvo2LHjHTw7W4QAzOfJjnX5+eBlLiRl8+W/53itf/kyYk9czeBaei4ataJcPUAFNzCajZxJOVOo5EpSThJyyQVv+WvYm1uQKd+CWZaDv5O/TbmVVn6taODeAIW8kqwNxeCqURFWx52wOrZxX5JkaeeVnmsgI8dAeq4+//8G0nMMZOQayMjVk55z87aB9Bw92XoTF5KyGfXtAX59ukOJ3SD+PHoVSYIO9T0qVH6kKugR4gN/nebI5aLdhTdTkPDg52KPeyXUpHS2VzF7UFNe+PU4Y9rXrVRX/Ii2gfx57CrrT8TxQF13zJKltEmtYvoQl4X63o4o5TIycg3EZ+aVuz1jdCWWgLmZfs39+PSfs+w5m2wtSK+Uy+jZxIfH2wTSrbF3pZRlsiE7BdY+A2e3WrabPQqDFoF91ViEBHc3Wq2Wc+fOWbcvXrxIeHg4Hh4eeHh4MHfuXB577DH8/Pw4f/48L7/8Mg0bNqRv374ANGnShH79+jF58mQWL16MwWBg6tSpjBw5koAAS5WF0aNHM3fuXCZNmsQrr7zCqVOnWLRoEf/3f/9nPe4LL7xAt27d+OSTTxg4cCC//vorR44cYcmSJXf2gtyEEID5qBRy3hjQhEk/HGHZf5cY064udTzLfhPdeMri/u0RUnH37/2EVq/lRMIJG6F3MvEkeca8QmPlMjnBXrVo6XMSX7UjfUIepU2tefg6VW8Nw6KQyWQ42ilxtFOWWRQkZuUx+tuDnEvUMmrJAX59uuNt35Nms2R1/9aU5I+bqe2uIdjXmZiELHadSSq2N3Vkgfu3EsqVFDAoNICeTXxwqOTPZNsgd4I8NVxKyeH9TZZKAj0qoRB5AXZKOQ28nYhJyCI6LqvCArC8PYBvR7CvM80CXDh9PZMG3o6MaBvI0LDalZ/dW8DlffDHJMi6Dgo76P8BPDBeuHwFt+XIkSP06NHDuj1z5kwAxo0bx9dff82JEyf44YcfSE9PJyAggD59+jB//nybuMIVK1YwdepUevbsiVwu57HHHuOzzz6zPu7q6srWrVuZMmUKDzzwAF5eXrz99tvWEjAAnTp1YuXKlbz55pu8/vrrNGrUiLVr11ZbDUAQAtCGh0J86NLIiz1nk1mwKYqvn3igTM+XJIlN+e7fAcL9WySSJBGnjSM8Ppyj146y+dJmZi2exfnU80gUzhB1VDnS0reljVWvuU/zcrlw7zZ8nO1ZObk9o5Yc4PxNlsCirHuHLqVyJTUHJzsl/VtUX0xJcTzUxIeYhCx2RCcWKwDL2gO4tGjUlf91J5PJGN4mkI+2xJCW37GmovX/biXE3yKco+IzyyUuU7P11tCDxqWIvywLMpmMFU+1JzFLRyMfp6pLdDKb4b+F8O97IJnAs5HF5etXfTdPwd1B9+7di60+sGXLlhLn8PDwsBZ9vh0tW7Zkz549xY4ZPnw4w4cPL/F4dwohAG9CJpPx5sCm9F+0m02n4jlwIaVM5VFOX8/kSmoO9ip5pQWB380YzUZikmOsFr2CbNyknKQixwc4BxTqhdvAowFy2f1brcjH2Z5fJndg5LcHuJCUzcglRYvAVUcs1r+BLfyrROhUBj1DfPh653l2xiRhNJlv6xqsrAzgO8WwB2rzydYYzBI4qhW0CarcmnMhfi78xfVyt4QrKKlT11NTJUlfbhp1sS79CqNNgjVPw/kdlu2WI2DgQrCr4jZyAsE9Ts28U1QjwX7OjGpXhxUHrzB/fWSRzeRvx6YC92+wT429CVcVWbosWxdufhauzlQ46UEhUxDiFUJLn5ao09Q83vVx2tRug49j5bnO7iV8XOz5dXIHRi45wIXkG5bA2u4WEajVGa2Fxyuj9VtVEVbHHTeNivQcA8eupBcq2wMWV3ZByZOmlegCrkp8XezpHuzDjuhEOjf0Qq2s3B8sBZ07ytsSrkA4Bley9e+OcHE3/PkUaBNA6QADP4ZWY4TLVyCoBO4vlVJKZvZuzLrw65y+nsmfx67yeJuSY6pssn/LWfz5bkCSJK5lXSuUmHE+7XyR453UTjZZuK38WtHMuxkOKgcMBgMbN26kd/3e1swpQdH4uNjzy9MWEXjRKgI7UsvNgY0n4sg1mKjv5cgDdStefLiqUMhl9Aj2Yc3xa2yPTihSAF5JzSFHb0KtlBNUQtJLTeLlfsEYzRLPP9So0udukp+5ez4pG53RVOb6gpXZA/iOYTbB7o9g1wcgmcE7xOLy9ak57SoFgrsdIQCLwNPJjmk9G/Huxig+2hLDgBb+OJXgOomOz+JicjZqpdza+upux2AyEJ0cbeO+DY8PJyW3cJ07gNoutW0KKYf5hVHPvd597cKtTHxd8t3BS/ZzKSUnPzGkA6uOWlq/DWtTu0Z0IymOHiEWAbgjKrHITPsC92+wr3PlZ49WISF+Lvw4sV2VzO3rYme1nJ5L1NIswLVMz49OKOgBfHe41MmKh9WTLdY/gFZPwIAPQX33/CAQCO4GhAC8DWM7WcrCXE7JYfHO88zqG1zs+ILiz90ae5coFmsiGXkZhVy4pxJPoTfpC41VyBQ09W5q6ZZxUyFlL035u54ISoef6w1L4OWUHIZ9vY/rGXnIZfBY65rr/i2gWyNvFHIZZxO1xKbmFIplvBH/dxdZq6oYmUxGiJ8zBy6kEh2XVSYBaDSZOVNFGcBVwvkdsPppyE4ClSM8vBBCR5b8PIFAUGbuPqVyh7BTKnh9QBP+99NRluyxtGIriLkqio35vX8H1NAMzAIkSSI2M7aQC/di+sUixzurnW3ct6G+oTTzaYa90v4Or1xQgL+rQ74l8IC1YHLXxt74utT818RVo6JNXXcOXkxlR3Qi4zoF2TweFV9QAuYusVbdIUL8XCwCsAxxgHkGE8//cpxcgwlXB1XNdqmbjLBzAez5BJDAp5nF5evduLpXJhDcswgBWAx9mvrSsb4n+y+k8P6maL4Y3brIcWcTsjiXqEWtkNOzSc2pRWcwGYhKjiok9tLy0oocH+gSWKiQcpBbkHDh1kAC3BzyLYH7iU3NZXQF2xfeSXo28eHgxVS2FyUA46qmY8XdThP/Gx1BSoNWZ2TyD0fYfyEFtVLOwsdDK9zjvMrIvG6p7Xdln2X7gQnQbwGoKqeYtkAgKBohAItBJpPx5sNNePjz/1h/Io4JnVN5oG7hwPWC5I8ujbzK3UKuoqTnpRMRH2ETq3c66XSRLlylXGlx4fqGEuobSph/GKG+oXhqSl/yRlD91HJz4O+pDxIdn1WmckXVzUMhvry3MZoD51PI1hmtpUky8wxcTbO096usdm33CgWCOKoUpWDSsvWMX3aIiKsZONkp+W5cm5r7/ji7Ddb8D3JSQO0Mgz6FFsOqe1UCwX2BEIAl0CzAlRFtAvn1cCzz/o5kzXOdkd/yS7qgBMedyP6VJIkrGVdsYvXC48O5lH6pyPGudq42sXqt/FrR1LspdsoqqtQvuKO4adQ19+Z+Gxp4O1LHQ8OV1Bz+O5dM32aWsImCciUBrva4akRW+M009nVGJoNkraWf9O06bcRl5PLk94c4l6jFw1HNDxPa0aJ22ZJG7ggmA+yYD3sXWbb9Wlpcvp7F94kWCASVhxCApeDFPsGsPxFHxNUM/oq4xtCwG8H25xK1xCRkoZTL6F3J7l+9SU9kUmShQsrpeelFjq/rWtcmVi/MP4y6rpXb+1QgqCgymYyHQnxYvu8S/0Yn3hCA8XdXAeg7iYNaQT1PRy4kZxMTn1WkALyYnM0T3x3kWnou/q72/DSpPQ19amCx5PRY+HMSxB60bLedDH3eAVXNj2EVCO4lhAAsBd7OdjzXowEfbo7hg00x9G3mZy30vDm/+HPnhl4Vslqk5abZuG/D48OJTIrEYDYUGquUK2nm3axQcoa7Q82tAScQ3EzPJhYBuCM6EbNZQi6X3dQC7i7IVq0GQvyduZCcTXR8Jg82ss24j7yeydilh0jW6qjn5chPk9oVm7RWbURvhLXPQl462LnC4M+h6eDqXpVAcF8iBGApmdi5HisPXuFqWi7f7LrAjN6W7LSC+L/SZv9KksTljMuFEjMuZ1wucnyBCzfML8wq9pp4NREuXMFdTbt6HjiqFSRm6Th9PZMWtV2JjBMZwMUR4ufCxpPxheIAj1xKZcLyw2TlGWnq78KPk9rh5VTDvh+MevhnDhz40rId0BqGLQWPetW6LIHgfkYIwFJir7KUhXluxTG+2X2eke0C0RnMRMZlopDL6N20sADUGXVEJkUWsuxl6DKKPEaQW5BNL9xQv1DhwhXck9gpFXRp5M3m0/Fsj06gaYALMcIFXCwFnTxuLgWzMyaRZ34+Sp7BTNsgd74f37baEtFuS9ol+GMiXDtq2e7wHPSaC8oq7B8sEAhKRAjAMtC/uR/tgjw4dCmVDzfH0Di/t2anBp4g1/LvxQibxIzIpEiMZmOheVRyFc18mhUSe272bnf4jASC6uOhEB82n45nR3Qij4QGkGcwY6+6u1rA3UkKhPHZBC1Gk5lNp+KZ+Xs4BpNE92Bvvh7zAA7qsrWJq3Ii18FfU0GXAfauMORrCBlY3asSCAQIAVgmCsrCDP5iL2uOX8PBTg+o2Z2wCM8PfynyOe727oVi9Zp4N0GtEL9+Bfc33UO8AThxNYPdZ5IASwu4Gluvrpqp5eaAk50Src7I+5ui+X7vRSQJBoUG8MnwUNTKGlSv06iDrW/CoSWW7dptLS5ft7unXqVAcK8jBGAx6Iw6TiedtnHfRiREoFJMwMnUm1ydGgkTV/UbQQb13evb9MJt5deKQJdA4cIVCIrAx9me0NquRFzN4Ns9lk40wv17e+RyGcF+zhy9nMZ3/1mu15j2dZg3uHnNEs0p5+GPCRAXYdnu/AI89BYoaphrWiC4zxECMJ+UnJRC5VaikqOKdOHa2/2KU25XkOyo46Xn5+F/09K3Ja72NbDelkBQg3koxJeIqxlcS7cUgBYCsHhC8gUgwJQeDZjVJ7hm/cA8tRrWTQN9Fjh4wNBvoHGf6l6VQCAogvtaAP5++nd+OvET4fHhXM28WuQYDwcPmwzcVn6tCPYMZsWBq8xdH8kb/TrTpW7VF4AWCO5Fejbx4f/+OWPdLkh0EBTNI6EB7IxJYuKD9Zj0YA3KoDXkwubX4Ogyy3adjvDY9+Baq3rXJRAIbst9LQDPp55n/Zn11u0G7g0K9cKt5VyryF/Y4zvXY0yHuqgUNSjuRiC4y2gW4IKPsx2JWToAQoQFsFja1/dk76sPVfcybEk+C6vGQ8IpQAZdZkL310FxX99eBIIaz339CR3YeCDOds608mtFS9+WuNiV7eYjxJ9AUDEKuoL8ejiWWm4OuDqIOLG7ihO/w9/TwZANGi94dAk07FndqxIIBKXgvhaALX1b0tK3ZXUvQyC4rxkaVovfj8TSPdi7upciKC36HNj0Mhz/ybId1AUe+w6cS1cQXyAQVD/3tQAUCATVT4Fb08NRlEa6K0iMtrh8k6IAGXR7Bbq9DPIaVoNQIBAUixCAAoGg2vF3dajuJQhKw/EVsOFFMOaCky88+i3U71bdqxIIBOVACECBQCAQFI9OCxtnQUR+wfv63S3iz8mnWpclEAjKjxCAAoFAILg9CactLt/kMyCTQ4/X4cEXQS6S4ASCuxkhAAUCgUBQGEmCYz/AplfAmAfO/pbafkGdq3tlAsF9RW5uLpIkodFoALh8+TJr1qyhadOm9OlT/kLr4iecQCAQCGzJy4Q/J8HfL1jEX8Pe8Mx/QvwJBNXA4MGD+fHHHwFIT0+nffv2fPLJJwwePJivv/663PMKASgQCASCG8RFwJJucOpPkCmg11wY/Ts4elX3ygSC+5Jjx47RpUsXAP744w98fX25fPkyP/74I5999lm55xUuYIFAIBBYXL6Hv4Mtr4NJDy61YdhSqNO+ulcmENzX5OTk4OxsaZO5detWHn30UeRyOR06dODy5cvlnldYAAUCgeB+Jy8DVo2zZPqa9NC4PzyzR4g/gaAG0LBhQ9auXUtsbCxbtmyxxv0lJibi4lL+9plCAAoEAsH9zLWjsLgLRP4FchX0fQ9G/QIaj+pemUAgAN5++21mzZpFUFAQ7du3p2PHjoDFGhgWFlbueYULWCAQCO5HJAkOLoatb4HZAG51YNhyqP1Ada9MIBDcxLBhw3jwwQeJi4sjNDTUur9nz54MHTq03PMKASgQCAT3Gzmp8NdUiNlg2W4yCB75AhzcqnVZAoGgMDt27KBTp074+dn22m7Xrl2F5hUCUCAQCO4nYg/DHxMgIxYUaujzLrSbDDJZda9MIBAUwSOPPILRaKRt27Z0796dbt260blzZxwcKtZCU8QACgQCwf2A2Qx7P4Nl/Sziz70eTNoK7Z8W4k8gqMGkpaWxfft2+vfvz6FDhxg6dChubm507tyZN998s9zzCgEoEAgE9zrZKfDLSNj2FpiN0OxR+N9uCCh/ALlAILgzqFQqOnfuzOuvv86WLVs4cOAAo0aN4tChQyxYsKDc8woBKBAIBPcyl/fDN13g7BZQ2MHD/2ep72df/vIRAsHdwu7duxk0aBABAQHIZDLWrl1rfcxgMPDKK6/QokULHB0dCQgIYOzYsVy/ft1mjqCgIGQymc3f+++/bzPmxIkTdOnSBXt7ewIDA/nwww8LrWXVqlWEhIRgb29PixYt2LhxY6nO4cyZMyxZsoTRo0dTq1YtunXrRkZGBh9//DHHjh0r+0XJR8QACgQCwb2I2Qx7/w92vAuSCTwbwvDl4NeiulcmENwxsrOzCQ0NZeLEiTz66KM2j+Xk5HDs2DHeeustQkNDSUtL44UXXuCRRx7hyJEjNmPnzZvH5MmTrdsFhZkBMjMz6dOnD7169WLx4sWcPHmSiRMn4ubmxtNPPw3Avn37GDVqFAsWLODhhx9m5cqVDBkyhGPHjtG8efNizyEkJARvb29eeOEFXn31VVq0aIGsEsI2hAAUCASCew1tEqx5Gs7vsGy3HAEDF4KdU/WuSyC4w/Tv35/+/fsX+Zirqyvbtm2z2ffFF1/Qrl07rly5Qp06daz7nZ2dC2XhFrBixQr0ej1Lly5FrVbTrFkzwsPDWbhwoVUALlq0iH79+vHSSy8BMH/+fLZt28YXX3zB4sWLiz2HadOmsXv3bubNm8f69evp3r073bt358EHH0Sj0ZT6WtyKcAELBALBvcTFPbD4QYv4UzpYyrsM/UaIP8E9Q1ZWFpmZmdY/nU5XaXNnZGQgk8lwc3Oz2f/+++/j6elJWFgYH330EUaj0frY/v376dq1K2q12rqvb9++xMTEkJaWZh3Tq1cvmzn79u3L/v37S1zTp59+yrFjx4iPj+e1115Dr9fzxhtv4OXlRefOnct9rsICKBAIBPcCZhPs/hh2vQ+SGbyC4fEfwKdJda9MIKhUmjZtarM9e/Zs5syZU+F58/LyeOWVVxg1apRNi7Vp06bRunVrPDw82LdvH6+99hpxcXEsXLgQgPj4eOrVq2czl6+vr/Uxd3d34uPjrftuHhMfH1/q9ZlMJgwGAzqdjry8PHQ6HTExMeU9XSEABQKB4K4nKwFWPwUXd1u2Wz0BAz4EtWP1rksgqAIiIyOpVauWddvOzq7CcxoMBh5//HEkSeLrr7+2eWzmzJnWf7ds2RK1Ws3//vc/FixYUCnHLolp06axc+dOIiMjcXd3p2vXrkyePJnu3bvTokX5Y3qFABQIBIK7mfP/wurJkJ0EKo0lyzd0ZHWvSiCoMpydnW0sdBWlQPxdvnyZHTt2lDh3+/btMRqNXLp0ieDgYPz8/EhISLAZU7BdEDd4uzG3iyu8mbi4OJ5++mm6d+9eYsJIWRACUCAQCO5GTEaLu3f3x4AEPs0sWb7ejat7ZQLBXUOB+Dt79iz//vsvnp6eJT4nPDwcuVyOj48PAB07duSNN97AYDCgUqkA2LZtG8HBwbi7u1vHbN++nenTp1vn2bZtGx07dizxeKtWrSrHmZWMSAIRCASCu43M6/DjI7D7I0CC1uNg8nYh/gSCW9BqtYSHhxMeHg7AxYsXCQ8P58qVKxgMBoYNG8aRI0dYsWIFJpOJ+Ph44uPj0ev1gCV549NPPyUiIoILFy6wYsUKZsyYwRNPPGEVd6NHj0atVjNp0iROnz7Nb7/9xqJFi2xcxy+88AKbN2/mk08+ITo6mjlz5nDkyBGmTp1aqvP46aef6Ny5MwEBAVy+fBmwJIf89ddf5b42QgAKBALB3cTZfyxZvpf3gtoJHvseHvkMVBXrCyoQ3IscOXKEsLAwwsIsXW9mzpxJWFgYb7/9NteuXWPdunVcvXqVVq1a4e/vb/3bt28fYIkv/PXXX+nWrRvNmjXj3XffZcaMGSxZssR6DFdXV7Zu3crFixd54IEHePHFF3n77betJWAAOnXqxMqVK1myZAmhoaH88ccfrF27tlQu3a+//pqZM2cyYMAA0tPTMZlMALi5ufHpp5+W+9oIF7BAIBDcDZgMsOMd2PupZduvBQz/ATwbVOuyBIKaTPfu3ZEk6baPF/cYQOvWrTlw4ECJx2nZsiV79uwpdszw4cMZPnx4iXPdyueff863337LkCFDbDqQtGnThlmzZpV5vgKEABQIBIKaTsZV+GMixB60bLedDH3eAZV99a5LIBBUORcvXrRaMG/Gzs6O7Ozscs9b7S7gL7/8kqCgIOzt7Wnfvj2HDh0qdnx6ejpTpkzB398fOzs7GjduXOp+egKBQHDXEbPJ4vKNPQh2Lhar38CPhfgTCO4T6tWrZ41hvJnNmzfTpEn563xWqwXwt99+Y+bMmSxevJj27dvz6aefWqtnF2TX3Ixer6d37974+Pjwxx9/UKtWLS5fvlyoYrdAIBDc7cjMRuT/vAUH82uSBYTBsGXgUa/4JwoEgnuKmTNnMmXKFPLy8pAkiUOHDvHLL7+wYMECvvvuu3LPW60CcOHChUyePJkJEyYAsHjxYjZs2MDSpUt59dVXC41funQpqamp7Nu3z5pqHRQUdCeXLBAIBFVP+mW6nH0HRc4Fy3aH56DXHFBWfdFZgUBQs3jqqadwcHDgzTffJCcnh9GjRxMQEMCiRYsYObL8NT+rTQDq9XqOHj3Ka6+9Zt0nl8vp1avXbXvjrVu3jo4dOzJlyhT++usvvL29GT16NK+88goKhaLI5+h0Ops+gVlZWYCl9o/BYKjEMxKUlYLrL16HmoF4PWoGsugNKNc/j7suE8nOFdOgz5GCB4AEiNfmjnMvfS4MBgOSZMJsNhU7TpJMNfIeWdPWcycZM2YMY8aMIScnB61WW6SXtKxUmwBMTk7GZDIV2RsvOjq6yOdcuHCBHTt2MGbMGDZu3Mi5c+d47rnnMBgMzJ49u8jnLFiwgLlz5xbav3v3biIjIyt+IoIKs23btupeguAmxOtRPcjNBppd/5X6SZbrn6ppwJF6U8g9D5wXcc7Vzb3wucjKyuL8NTn2js7FjsvLzmJb3nmcnYsfd6dJTk6u7iVUOxqNBo1GUylz3VVZwGazGR8fn/9v787joqreB45/hoFhRyRlc99XFJc0KtdQXNNcsjT3NE1LwdxKhbTULM1yI3f7/jRLMys1FEk0EytNct9RssQNkUWBgbm/P+bLfB1BZIZlWJ736zWvPPeee+5z54g83XPvOaxcuRK1Wk2LFi34559/+Pjjjx+bAE6fPt1oMsZ//vmHhg0b0rZtWxk+tjCtVkt4eDidOnUyDOkLy5H+sKC7Mai3vY7Vrb8A0D49loPap/Hv3FX6wsJK089FfHw8Mb9cxsHZNdd695MS6NSmJm5ubkUTWB5duXLF0iEUmebNmxMREUH58uVp1qwZKpXqsXX//PNPs85hsQSwQoUKqNVqk9bG8/LywsbGxmi4t0GDBoZZuzUaTbZjbG1tjRZrTkxMBMDGxqbE/zCXFtIXxYv0RxE7uQ1+eBvSk8DeDV4KhRodUXbtkr4oRkpDX9jY2KBSqbGyyvmRqSwqlbpYXm9xi6cw9erVy5C79OrVK9cE0FwWSwA1Gg0tWrQgIiKC3r17A/o7fBEREY9dGuW5555j06ZN6HQ6rKz0M9icP38eLy+vHJM/IYQotrSpsHs6HFmrL1f106/qUa6SPOsnRBn38KhmSEhIoZzDovMABgUFsWrVKjZs2MCZM2cYO3YsKSkphreChwwZYvSSyNixY4mPj2fChAmcP3+enTt3MnfuXMaNG2epSxBCCNPdvgir/f+X/D0fBEN36JM/IYR4yOuvv05kZGSBt2vRZwAHDBjArVu3mDVrFnFxcfj6+hIWFmZ4MSQ2NtZwpw+gSpUq7N69m8DAQJo0aUKlSpWYMGECU6dOtdQlCCGEaY5/Az9OBG0KOFSAPl9AbX9LRyWEKKZu3bpFly5dqFixIq+88gqvvfYaTZs2zXe7Fn8JZPz48Y8d8s0p4/Xz88vTunxCCFGspN+Hn6bAsf/oy9XbQJ9V4OJl2biEEMXa999/z927d9myZQubNm1i0aJF1K9fn0GDBjFw4ECzX2i1+FJwQghR6t08C6s6/jf5U0G7qTDke0n+hBB5Ur58eUaPHk1kZCRXr15l2LBh/Oc//6F27dpmt2nxO4BCCFGqHdsIu94B7X1wdIe+q6FmO0tHJYQogbRaLUeOHOG3337jypUr2eZSNkWB3gF88OBBQTYnhBAlV1oyfDcGvn9Tn/zVbA9jf5XkTwhhsn379jFq1Cg8PDwYNmwYLi4u7Nixg2vXrpndZoHcAUxLS2Pp0qV8/PHHxMXFFUSTQghRct04BVuGwe3zoLKC9u9CmyB4wvxrQgjxqEqVKhEfH0+XLl1YuXIlPXv2NJrf2Fx5TgDT0tIICQkhPDwcjUbDlClT6N27N+vWreO9995DrVYTGBiY74CEEKLEUhT480v9yx4ZqeDspR/yrf68pSMTQpRQISEh9O/fH1dX1wJtN88J4KxZs/jiiy/w9/fn0KFD9O/fn+HDh3P48GEWLVpE//79jVboEEKIMiUtST+9y8mt+nJtf3jpC3CsYNGwhBAl26hRowC4ePEily5dom3bttjb26MoSr5WCMlzArhlyxa+/PJLXnzxRU6ePEmTJk3IyMjgr7/+KpQlSoQQosS4flw/5Bt/CVRqeGEmPDsBrGSiBSFE/ty5c4eXX36Zffv2oVKpuHDhAjVr1mTkyJGUL1+ehQsXmtVunv91unbtGi1atACgcePG2NraEhgYKMmfEKLsUhT4Y7V+VY/4S+BSGYb/BM8HSvInhCgQgYGB2NjYEBsbi4ODg2H7gAEDCAsLM7vdPN8BzMzMNFpv19raGicnJ7NPLIQQJVrqPfjhbTi9XV+u2xV6LwcHN4uGJYQoXfbs2cPu3bupXLmy0fY6depw9epVs9vNcwKoKArDhg0zvHmSmprKmDFjcHR0NKq3bds2s4MRQogS4Z8/YetwuHsFrKzB/33wGwcyIiKEKGApKSlGd/6yxMfH5+tt4DwngEOHDjUqv/baa2afVAghSiRFgd++gD0zQKeFclWh/zqo3NLSkQlR4HQ6HQkJCXmq6+rqipU89lAo2rRpw5dffsmcOXMAUKlU6HQ6FixYQIcOHcxuN88J4Lp168w+iRBClHgP7sL34+HsDn25fg/otRTsy1s2LiEKSUJCAot2HMPO0TnXeqkpSQT1aIabmzz+UBgWLFjACy+8wJEjR0hPT2fKlCmcOnWK+Ph4fv31V7PblaXghBDiSa4dgS3D4V4sqDXQ+QNoNVqGfEWpZ+fojKOLq6XDKNMaN27M+fPnWbp0Kc7OziQnJ9OnTx/GjRuHl5f564lLAiiEEI+j08HhZbA3BHQZUL469F8P3s0sHJgQoizQarV06dKF0NBQ3nvvvQJtWxJAIYTIyf14/Vq+F3bry41egp6fgV05y8YlhCgzbGxsOH78eKG0LU9sCiHEo2IPQ+jz+uRPbQvdF0G/dZL8CSGK3GuvvcaaNWsKvF25AyiEEFl0Ovh1Mfz8ASiZ8FRt/ZCvp4+lIxNClFEZGRmsXbuWvXv30qJFi2zT7y1atMisdvOUAP7www95bvDFF180KxAhhLCo5Fvw3RtwKUJf9nkZeiwC29zfgBRCiMJ08uRJmjdvDsD58+eN9hX6WsC9e/fOU2MqlYrMzEyzgxFCCIu4chC2joTkOLC2h24LoNlgectXCGFx+/btK5R285QA6nS6Qjm5EEJYlC4TflkIkfNA0UGFevohX4+Glo5MCCEKlTwDKIQom5JuwLZRELNfX/YdBN0+Bo1j7scJIUQpYFYCmJKSwv79+4mNjSU9Pd1o39tvv10ggQkhRKG5HAnfjoKUm2DjoH/L1/dVS0clhBBFxuQE8NixY3Tr1o379++TkpKCm5sbt2/fxsHBAXd3d0kAhRDFV2YG7P8IDnwMKODeUD/kW7GepSMTQogiZfI8gIGBgfTs2ZO7d+9ib2/P4cOHuXr1Ki1atOCTTz4pjBiFECL/Eq/Dly/CgQWAAs2HwqifJfkTQhQ7zZs35+7duwDMnj2b+/fvF/g5TE4Ao6OjmTRpElZWVqjVatLS0qhSpQoLFizg3XffLfAAhRAi3y7shdDn4OqvoHGCPqvhxc/Bxt7SkQkhCtGBAwfo2bMn3t7eqFQqtm/fbrRfURRmzZqFl5cX9vb2+Pv7c+HCBaM68fHxDBo0CBcXF1xdXRk5ciTJyclGdY4fP06bNm2ws7Mz5ESP2rJlC/Xr18fOzg4fHx927dr12LjPnDlDSkoKAO+//3628xUEk4eAbWxssLLS543u7u7ExsbSoEEDypUrx99//13gAQohhNkyM2DfB3DwU33Zw0c/5FuhtkXDEkIUjZSUFJo2bcqIESPo06dPtv0LFizg888/Z8OGDdSoUYOZM2cSEBDA6dOnsbOzA2DQoEFcv36d8PBwtFotw4cPZ/To0WzatAmAxMREOnfujL+/P6GhoZw4cYIRI0bg6urK6NGjATh06BCvvvoq8+bNo0ePHmzatInevXvz559/0rhx42xx+fr6Mnz4cJ5//nkUReGTTz7Byckpx2ucNWuWWd+NyQlgs2bN+OOPP6hTpw7t2rVj1qxZ3L59m//85z85XoQQQljEvWv6uf3+PqwvP/06dP4QbOwsG5cQosh07dqVrl275rhPURQWL17MjBkz6NWrFwBffvklHh4ebN++nVdeeYUzZ84QFhbGH3/8QcuWLQFYsmQJ3bp145NPPsHb25uNGzeSnp7O2rVr0Wg0NGrUiOjoaBYtWmRIAD/77DO6dOnC5MmTAZgzZw7h4eEsXbqU0NDQbLGtX7+e4OBgduzYgUql4qeffsLaOnvKplKpzE4ATR4Cnjt3Ll5eXgB8+OGHlC9fnrFjx3Lr1i1WrlxpVhBCCFGgzoXp1/L9+zDYuujv+nVfKMmfEKVAUlISiYmJhk9aWppZ7cTExBAXF4e/v79hW7ly5WjdujVRUVEAREVF4erqakj+APz9/bGysuK3334z1Gnbti0ajcZQJyAggHPnzhme44uKijI6T1adrPM8ql69emzevJk//vgDRVGIiIjg2LFj2T5//vmnWdcOZtwBfPhLcHd3JywszOyTCyFEgcpIh4j3IWqpvuzlC/3XgVtNi4YlhCg4DRsaT9QeHBxMSEiIye3ExcUB4OHhYbTdw8PDsC8uLg53d3ej/dbW1ri5uRnVqVGjRrY2svaVL1+euLi4XM+Tm8JajEMmghZClA53r8LWEfDPEX259Vjo9D5Y21o2LiFEgTp9+jSVKlUylG1tS//P+KVLl1i8eDFnzpwB9EnwhAkTqFWrltltmpwA1qhRI9fFhy9fvmx2MEIIYZYzO+D7NyH1HtiVg17LoUEPS0clhCgEzs7OuLi45LsdT09PAG7cuGF4tC2r7Ovra6hz8+ZNo+MyMjKIj483HO/p6cmNGzeM6mSVn1Qna39udu/ezYsvvoivry/PPfccAL/++iuNGjXixx9/pFOnTnm9ZCMmJ4ATJ040Kmu1Wo4dO0ZYWJjh4UYhhCgSGWkQPgt+++9D1JVaQr+1UL6aZeMSQhR7NWrUwNPTk4iICEPCl5iYyG+//cbYsWMB8PPzIyEhgaNHj9KiRQsAfv75Z3Q6Ha1btzbUee+999BqtdjY2AAQHh5OvXr1KF++vKFORESEUQ4VHh6On5/fE+OcNm0agYGBzJ8/P9v2qVOnFl0COGHChBy3L1u2jCNHjpgVhBBCmCz+MmwZDtej9WW/8fBCMFhrcj1MCFF2JCcnc/HiRUM5JiaG6Oho3NzcqFq1KhMnTuSDDz6gTp06hmlgvL296d27NwANGjSgS5cujBo1itDQULRaLePHj+eVV17B29sbgIEDB/L+++8zcuRIpk6dysmTJ/nss8/49NNPDeedMGEC7dq1Y+HChXTv3p3Nmzdz5MiRPL08e+bMGb755pts20eMGMHixYvN/m5Mfgv4cbp27cq3335bUM0JIcTjnfoOvminT/7sy8OrX0PAh5L8CSGMHDlyhGbNmtGsWTMAgoKCaNasmWHqlClTpvDWW28xevRonn76aZKTkwkLCzPMAQiwceNG6tevzwsvvEC3bt14/vnnjRK3cuXKsWfPHmJiYmjRogWTJk1i1qxZhilgAJ599lk2bdrEypUradq0KVu3bmX79u15mj6vYsWKREdHZ9seHR2d7QUVUxTYSyBbt27Fzc2toJoTQojstKmw+104skZfrvIM9FsD5SpbNi4hRLHUvn17FEV57H6VSsXs2bOZPXv2Y+u4ubkZJn1+nCZNmvDLL7/kWqd///70798/94BzMGrUKEaPHs3ly5d59tlnAf0zgB999BFBQUEmt5fFrImgH34JRFEU4uLiuHXrFsuXLzc7ECGEyNXti7BlGNw4oS8/HwQd3gW1jUXDEkKIwjRz5kycnZ1ZuHAh06dPB8Db25uQkBDefvtts9s1OQHs1auXUQJoZWVFxYoVad++PfXr1zc7ECGEeKzjW2DHREhPBocK0OcLqO3/xMOEEKKkU6lUBAYGEhgYSFJSEqB/Ezq/TE4AzZlsUQghzJJ+H8Kmwp9f6svVnoe+q8HFK/fjhBCiFCqIxC+LyS+BqNXqbHPiANy5cwe1Wl0gQQkhBLfOweoX/pv8qaDdVBjyvSR/QghRAEy+A/i4hynT0tKM1sETQgizRW+CnZNAex8c3aHvKqjZ3tJRCSFEqZHnBPDzzz8H9GPRq1evxsnJybAvMzOTAwcOyDOAQoj8SU+Bne/AX/99465GO+izCpw9cj9OCCGESfKcAGZNaKgoCqGhoUbDvRqNhurVqxMaGlrwEQohyoYbp2HLULh9HlRW0H46tJkEVvJoiRCibNJqtXTp0oXQ0FDq1KlToG3nOQGMiYkBoEOHDmzbts2wvIkQQuSLouif8/tpCmSkgrOX/kWP6s9bOjIhhLAoGxsbjh8/Xihtm/wM4L59+wojDiFEWZSWBDsC4cQWfbnWC9BnJThWsGxcQgiz6HQ6EhIS8lTX1dUVK6sCW5Cs1HrttddYs2ZNtrWA88vkBLBv3760atWKqVOnGm1fsGABf/zxB1u2bCmw4IQQpdj147B1ONy5CCo1dJwBz00E+YUgRImVkJDAoh3HsHPMfbqS1JQkgno0kxXE8iAjI4O1a9eyd+9eWrRogaOjo9H+RYsWmdWuyQnggQMHcpwLsGvXrixcuNCsIIQQZYii6JdyC3sXMtPApRL0WwtVn7F0ZEKIAmDn6Iyji6ulwyg1Tp48SfPmzQE4f/680b6HF+YwlckJYHJyco7TvdjY2JCYmGh2IEKIMiD1Hvw4AU59py/X7QK9V4CD3AUQQoicFNajdyaPtfj4+PD1119n275582YaNmxYIEEJIUqhf4/BF231yZ+VNXT+EF7dLMmfEELkwcWLF9m9ezcPHjwAHj8vc16ZfAdw5syZ9OnTh0uXLtGxY0cAIiIi+Oqrr+T5PyFEdooCv6+EPTMgMx3KVYX+66ByS0tHJoQQxd6dO3d4+eWX2bdvHyqVigsXLlCzZk1GjhxJ+fLlzX78zuQ7gD179mT79u1cvHiRN998k0mTJnHt2jX27t1L7969zQpCCFFKPbgLX7+mn+IlMx3q94AxByT5E0KIPAoMDMTGxobY2FgcHBwM2wcMGEBYWJjZ7Zp8BxCge/fudO/ePdv2kydP0rhxY7ODEUKUIteOwJbhcC8WrGyg8wfQ+g3Ix0PLQghR1uzZs4fdu3dTuXJlo+116tTh6tWrZreb7/kWkpKSWLlyJa1ataJp06b5bU4IUdIpChxaAmsD9Mlf+eowcg88M0aSPyGEMFFKSorRnb8s8fHx2Nramt2u2QnggQMHGDJkCF5eXnzyySd07NiRw4cPmx2IEKIUuB8PX72if95PlwENe8MbB6BSc0tHJoQQJVKbNm348ssvDWWVSoVOp2PBggV06NDB7HZNGgKOi4tj/fr1rFmzhsTERF5++WXS0tLYvn27vAEsRFkXexi2joTEa6C2hS5zoeVIuesnhBD5sGDBAl544QWOHDlCeno6U6ZM4dSpU8THx/Prr7+a3W6e7wD27NmTevXqcfz4cRYvXsy///7LkiVLzD6xEKKU0Ongl0Wwrps++XOrBa/vhadfl+RPCCHyqXHjxpw/f57nn3+eXr16kZKSQp8+fTh27Bi1atUyu9083wH86aefePvttxk7dix16tQx+4RCiFIk5TZ89wZc3Ksv+/SHHp+Cbe7LQAkhhMi7cuXK8d577xVom3lOAA8ePMiaNWto0aIFDRo0YPDgwbzyyisFGowQogS58it8OxKSroO1HXT7GJoNlrt+QghRwO7evcuaNWs4c+YMAA0bNmT48OH5Wks5z0PAzzzzDKtWreL69eu88cYbbN68GW9vb3Q6HeHh4SQlJZkdhBCiBNFlwv6PYUMPffJXoS6M2gfNh0jyJ4QQBezAgQNUr16dzz//nLt373L37l0+//xzatSowYEDB8xu1+S3gB0dHRkxYgQHDx7kxIkTTJo0ifnz5+Pu7s6LL75odiBCiBIg6Qb85yXY9wEoOmg6EEZHgoe8BCaEEIVh3LhxDBgwgJiYGLZt28a2bdu4fPkyr7zyCuPGjTO73XzNA1ivXj0WLFjAtWvX+Oqrr/LTlBCiuLscCaHPQ8x+sHGA3ivgpRWgcbR0ZEIIUWpdvHiRSZMmoVarDdvUajVBQUFcvHjR7HbzPRF0ViC9e/fmhx9+KIjmhBDFiS4T9s2FL3tDyk1wb6gf8vUdaOnIhBCi1GvevLnh2b+HnTlzJl8LcJi1FJwQooxIvA7fvg5XD+rLzYdAl49Ak31WeiGEEAXj+PHjhj+//fbbTJgwgYsXL/LMM88AcPjwYZYtW8b8+fPNPockgEKInF3cC9vegPu3QeMEPRZDk/6WjkoIIUo9X19fVCoViqIYtk2ZMiVbvYEDBzJgwACzzlEgQ8D5tWzZMqpXr46dnR2tW7fm999/z9NxmzdvRqVS0bt378INUIiyRJcBe0Pg//rqkz8PHxi9X5I/IYQoIjExMVy+fJmYmJhcP5cvXzb7HBa/A/j1118TFBREaGgorVu3ZvHixQQEBHDu3Dnc3d0fe9yVK1d45513aNOmTRFGK0TpZpd+B/V/esG13/QbWo6EgLlgY2fZwIQQogypVq1aoZ/D4gngokWLGDVqFMOHDwcgNDSUnTt3snbtWqZNm5bjMZmZmQwaNIj333+fX375hYSEhCKMWIjSSXVhDx3OzsAqMwVsXaDnZ9C4j6XDEkKIMu/ff//l4MGD3Lx5E51OZ7Tv7bffNqtNiyaA6enpHD16lOnTpxu2WVlZ4e/vT1RU1GOPmz17Nu7u7owcOZJffvkl13OkpaWRlpZmKGdNWK3VatFqtfm8ApEfWd+/9IOFZWqxivwA68PL9EWPJuj6roHyNUD6xiLkZ6P4KE19odVqUZRMdLrMXOspSqbhek2pn/Ux9RhT4i+L1q9fzxtvvIFGo+Gpp55C9dCE+yqVqmQmgLdv3yYzMxMPDw+j7R4eHpw9ezbHY7KWpIuOjs7TOebNm8f777+fbfuBAwc4ffq0yTGLghceHm7pEMos+/TbtIxZhtv9SwBcqtiZ054D0EWdAbJPOyCKlvxsFB+loS+SkpK49I8Vdo65r9WdmpJEeOp//00wob6zs7PJ53B2zvu64bdv385z3dJk5syZzJo1i+nTp2NlVXCvblh8CNgUSUlJDB48mFWrVlGhQoU8HTN9+nSCgoIM5X/++YeGDRvStm1bqlevXkiRirzQarWEh4fTqVMnbGxsLB1OmaM6twv1jvdRpd5DsStHepdFnLxqI/1RDMjPRvFRmvoiPj6emF8u4+Dsmmu9+0kJdGpTE8Ck+m5ubiafw5S1bK9cuZLnuqXJ/fv3eeWVVwo0+QMLJ4AVKlRArVZz48YNo+03btzA09MzW/1Lly5x5coVevbsadiWNRZubW3NuXPnqFWrltExtra22NraGsqJiYkA2NjYlPgf5tJC+qKIZaRBeDD8tkJfrtQCVb91WDl5w9Vd0h/FiPRF8VEa+sLGxgaVSo2VlTrXeiqV2nCtptTP+ph6jCnxl0UjR45ky5Ytj30vwlwWnQZGo9HQokULIiIiDNt0Oh0RERH4+fllq1+/fn1OnDhBdHS04fPiiy/SoUMHoqOjqVKlSlGGL0TJEx8Dazr/L/nzGw/Dw6B84b9xJoQQRal69eqoVKpsn6z1c9u3b59t35gxY4zaiI2NpXv37jg4OODu7s7kyZPJyMgwqhMZGUnz5s2xtbWldu3arF+/vkCvY968eezfv5/27dvz1ltvERQUZPQxl8WHgIOCghg6dCgtW7akVatWLF68mJSUFMNbwUOGDKFSpUrMmzcPOzs7GjdubHS8q6srQLbtQohHnNoOP7wFaYlgX16/lm+9rpaOSgghCsUff/xBZub/XkY5efIknTp1on///81pOmrUKGbPnm0oOzj8b5WjzMxMunfvjqenJ4cOHeL69esMGTIEGxsb5s6dC+jn6+vevTtjxoxh48aNRERE8Prrr+Pl5UVAQECBXMe8efPYvXs39erVA8j2Eoi5LJ4ADhgwgFu3bjFr1izi4uLw9fUlLCzM8GJIbGxsgY97C1GmaFNhz3vwx2p9uUpr6LcWylW2bFxCiDJPp9PleSq3R6c/eZKKFSsalefPn0+tWrVo166dYZuDg0OOj5wB7Nmzh9OnT7N37148PDzw9fVlzpw5TJ06lZCQEDQaDaGhodSoUYOFCxcC0KBBAw4ePMinn35aYAngwoULWbt2LcOGDSuQ9rJYPAEEGD9+POPHj89xX2RkZK7HFvStViFKlTuXYMtQiDuhLz8fCB3eA3XZfJZGCFG8JCQksGjHsTy9NdzXJ+8vjDwqPT2d//u//yMoKMjortnGjRv5v//7Pzw9PenZsyczZ8403AWMiorCx8fHaKaSgIAAxo4dy6lTp2jWrBlRUVH4+/sbnSsgIICJEyeaHeujbG1tee655wqsvSzFIgEUQhSCE1vhxwmQngwOT8FLK6GO/5OPE0KIImTn6Iyji2ue6yclJRle6ITsL3vmZPv27SQkJBjdRRs4cCDVqlXD29ub48ePM3XqVM6dO8e2bdsAiIuLy3Gauqx9udVJTEzkwYMH2Nvb5/m6HmfChAksWbKEzz//PN9tPUwSQCFKG+0D+Gkq/LlBX672HPRdDS7elo1LCCEKQMOGDY3KwcHBhISE5HrMmjVr6Nq1K97e//t3cPTo0YY/+/j44OXlxQsvvMClS5eyzShiSb///js///wzO3bsoFGjRtnehs5KWE0lCaAQpcmt8/oh35unARW0nQztpoJaftSFEKXD6dOnqVSpkqH8pLt/V69eZe/evU9MlFq3bg3AxYsXqVWrFp6envz+++9GdbKmrct6btDT0zPHqexcXFwK5O4f6F927dOn4JfllN8KQpQW0V/BziDQ3gdHd+izEmp1sHRUQghRoJydnXFxcclz/XXr1uHu7k737t1zrZe1wpiXlxcAfn5+fPjhh9y8eRN3d3dAvyKMi4uL4S6kn58fu3btMmonPDw8x6nszLVu3boCa+th8nqtECVdegpsfxO2j9EnfzXawpiDkvwJIco8nU7HunXrGDp0KNbW/7vndenSJebMmcPRo0e5cuUKP/zwA0OGDKFt27Y0adIEgM6dO9OwYUMGDx7MX3/9xe7du5kxYwbjxo0z3HUcM2YMly9fZsqUKZw9e5bly5fzzTffEBgYaJHrNYXcARSiJLtxGrYMg9vnQGUF7adDm0nwhFn4hRCiLNi7dy+xsbGMGDHCaLtGo2Hv3r2GuYerVKlC3759mTFjhqGOWq1mx44djB07Fj8/PxwdHRk6dKjRvIE1atRg586dBAYG8tlnn1G5cmVWr15dYFPAZJ0jt/n+Ll++bFa7kgAKURIpChz7D+yaAhkPwMlT/6JHjTaWjkwIIYqNzp07oyhKtu1VqlRh//79Tzy+WrVq2YZ4H9W+fXuOHTtmdoxP8uiUMlqtlmPHjhEWFsbkyZPNblcSQCFKmrQk2BEEJ77Rl2t11E/x4lQx9+OEEGbR6XTEx8fnaS1aV1dXWbxAFKgJEybkuH3ZsmUcOXLE7HYlARSiJIk7oR/yvXMRVGroOAOemwjyC0eIQpOSksJnP/2Fg7NrrvVSU5II6tEMNzfzJywWIq+6du3K9OnTzX5JRBJAIUoCRYEjayFsOmSmgUsl6LsGqhXcm2ZCiMezdzJtsmIhCtvWrVvz9T8bkgAKUdylJsKPb8Op7/TlOgHQewU4PmXZuIQQQhS6Zs2aGb0EoigKcXFx3Lp1i+XLl5vdriSAQhRn/x6DLcPhbgxYWYN/CDwzToZ8hRCijOjdu7dR2crKiooVK9K+fXvq169vdruSAApRHCkK/L4S9syAzHQoVxX6rYUqT1s6MiGEEEUoODi4UNqVBFCI4ubBXfh+PJzdoS/X7wG9loJ9ecvGJYQQotSQBFCI4uTaUdg6DBJiwcoGOn8Ard+AXCYBFUIIUfpYWVnlOgE0gEqlIiMjw6z2JQEUojhQFIhaBnuDQZcB5atDv3VQqbmlIxNCCGEB33333WP3RUVF8fnnn6PT6cxuXxJAISztfrx+Ld/zP+nLDXvBi0vArpxl4xJCCGExvXr1yrbt3LlzTJs2jR9//JFBgwYZLUtnKnmVUAhLiv0NQtvokz+1LXRfCP03SPInhBDC4N9//2XUqFH4+PiQkZFBdHQ0GzZsoFq1ama3KXcAhbAEnQ4OfQYRc0DJBLda0H89eDWxdGRCCCGKiXv37jF37lyWLFmCr68vERERtGlTMGu+SwIoRFFLuQ3fjYGL4fpy437QczHYOls0LCGEEMXHggUL+Oijj/D09OSrr77KcUg4PyQBFKIoXfkVvh0JSdfB2g66fgTNh8pbvkIIIYxMmzYNe3t7ateuzYYNG9iwYUOO9bZt22ZW+5IAClEUdJnwyyKInAuKDirU1Q/5ejSydGRCCCGKoSFDhjxxGpj8kARQiMKWfBO2jYLLkfpy01eh2ydg62TRsIQQQhRf69evL9T2JQEUojBd3q9P/pJvgI2DPvFrNsjSUQlRbOl0OhISEvJU19XVFStZF1sIs0gCKERh0GXC/o9g/wJAgYoN9EO+7uYv3C1EWZCQkMCiHcewc8z9pajUlCSCejTDzc2tiCITonSRBFCIgpZ4XX/X78ov+nKzwdB1AWgcLBuXECWEnaMzji6ulg5DiFJNEkAhCtLFCNg2Gu7fBhtH/fQuTV62dFRCCCGEEUkAhSgImRmw70M4uEhf9vDRD/lWqG3RsIQQQoicSAIoRH7d+0c/t19slL7ccgQEzAUbe8vGJYQQQjyGJIBC5Mf5PfDdG/AgHjTO8OLn0LiPpaMSQgghciUJoBDmyNRCxGw49Lm+7NUU+q2Dp2pZNi4hhBAiDyQBFMJUCbGwdQRc+0NfbvUGdJ4D1raWjUsIIYTII0kAhTDF2Z2w/U1ITQDbctBrKTR80dJRCSGEECaRBFCIvMhIh/BZ8NsKfblSC+i3FspXt2hYQgghhDkkARTiSeJjYOtw+PeYvuw3Hl4IBmuNZeMSQgghzCQJoBC5ObUdfngL0hLBzhVeCoV6XS0dlRBCCJEvkgAKkRNtKux5D/5YrS9XaQ1914BrFcvGJYQQQhQASQCFeNSdS7BlGMQd15efmwgdZ4DaxpJRCSGEEAVGEkAhHnZiK/w4AdKTweEpeOkLqNPJ0lEJIYQQBUoSQCEAtA8gbBocXa8vV30W+q0BF2+LhiWEEEIUBkkAhbh1Xj/ke/MUoIK270C7aaCWHw8hhBClk/yGE2XbX5thRxBoU8CxIvRZCbU6WjoqIYQQolBJAijKpvQU2DUFov9PX67RFvqsAmdPy8YlhBBCFAErSwcgRJG7eQZWddQnfyoraP8uDN4uyZ8QQpQiISEhqFQqo0/9+vUN+1NTUxk3bhxPPfUUTk5O9O3blxs3bhi1ERsbS/fu3XFwcMDd3Z3JkyeTkZFhVCcyMpLmzZtja2tL7dq1Wb9+fVFcXr5JAijKDkWBP/8DKzvArbPg5AlDfoD2U8FKbenohBBCFLBGjRpx/fp1w+fgwYOGfYGBgfz4449s2bKF/fv38++//9KnTx/D/szMTLp37056ejqHDh1iw4YNrF+/nlmzZhnqxMTE0L17dzp06EB0dDQTJ07k9ddfZ/fu3UV6neaQIWBRNqQlw45AOPGNvlyrI7y0EpwqWjYuIYQQhcba2hpPz+yjO/fu3WPNmjVs2rSJjh31z32vW7eOBg0acPjwYZ555hn27NnD6dOn2bt3Lx4eHvj6+jJnzhymTp1KSEgIGo2G0NBQatSowcKFCwFo0KABBw8e5NNPPyUgIKBIr9VUcgdQlH5xJ2BlO33yp1LDC7Ng0LeS/AkhRAmUlJREYmKi4ZOWlvbYuhcuXMDb25uaNWsyaNAgYmNjATh69CharRZ/f39D3fr161O1alWioqIAiIqKwsfHBw8PD0OdgIAAEhMTOXXqlKHOw21k1clqoziTBFCUXooCR9bCqhfgzkVw9oZhO6HNJLCSv/pCCFESNWzYkHLlyhk+8+bNy7Fe69atWb9+PWFhYaxYsYKYmBjatGlDUlIScXFxaDQaXF1djY7x8PAgLi4OgLi4OKPkL2t/1r7c6iQmJvLgwYOCuNxCI0PAonRKTdSv6HFqm75cpzP0DgXHpywblxBCiHw5ffo0lSpVMpRtbW1zrNe1a1fDn5s0aULr1q2pVq0a33zzDfb29oUeZ3Ent0FE6fNvNHzRVp/8WVlDpznw6teS/AkhRCng7OyMi4uL4fO4BPBRrq6u1K1bl4sXL+Lp6Ul6ejoJCQlGdW7cuGF4ZtDT0zPbW8FZ5SfVcXFxKfZJpiSAovRQFPhtJazpBHdjoFwVGP4TPPe2DPkKIUQZl5yczKVLl/Dy8qJFixbY2NgQERFh2H/u3DliY2Px8/MDwM/PjxMnTnDz5k1DnfDwcFxcXGjYsKGhzsNtZNXJaqM4kyFgUTo8SIAfxsOZH/Xlet2h11JwcLNoWEIIISzjnXfeoWfPnlSrVo1///2X4OBg1Go1r776KuXKlWPkyJEEBQXh5uaGi4sLb731Fn5+fjzzzDMAdO7cmYYNGzJ48GAWLFhAXFwcM2bMYNy4cYa7jmPGjGHp0qVMmTKFESNG8PPPP/PNN9+wc+dOS156nkgCKEq+a0dh6zBIiAUrG+g8B1qPAZXK0pEJIYSwkGvXrvHqq69y584dKlasyPPPP8/hw4epWFE/A8Snn36KlZUVffv2JS0tjYCAAJYvX244Xq1Ws2PHDsaOHYufnx+Ojo4MHTqU2bNnG+rUqFGDnTt3EhgYyGeffUblypVZvXp1sZ8CBiQBFCWZosDh5RAeDDotuFaD/uugUgtLRyaEEIVOp9Nle4YtJ66urliVwcdgNm/enOt+Ozs7li1bxrJlyx5bp1q1auzatSvXdtq3b8+xY8fMitGSJAEUJdP9eNj+Jpz/SV9u8CK8uATsXS0alhBCFJWEhAQW7TiGnaPzY+ukpiQR1KMZbm7yOIwwJgmgKHlif4OtIyDxGqg1EDAXnn5dhnyFEGWOnaMzji6ulg5DlECSAIqSQ6eDQ59DxGxQMsGtJvRfD15NLR2ZEEIIUaJIAihKhpTb8N0YuBiuLzfuCz0Wg52LRcMSQgghSiJJAEXxd/WQfsg36TpY20HXj6D5UBnyFUIIIcwkCaAovnQ6OLgQ9s0FRQdP1dEP+Xo2tnRkQgghRIkmCaAonpJvwrbRcHmfvtzkFei+EGydLBuXEEIIUQpIAiiKn8v7YdsoSL4B1vbQ/RPwHSRDvkIIIUQBkQRQFB+6TNi/APZ/BChQsYF+yNe9vqUjE0IIIUqVYjE1+LJly6hevTp2dna0bt2a33///bF1V61aRZs2bShfvjzly5fH398/1/qihEiKgy97wf75gALNXoNRP0vyJ4QQQhQCiyeAX3/9NUFBQQQHB/Pnn3/StGlTAgICuHnzZo71IyMjefXVV9m3bx9RUVFUqVKFzp07888//xRx5KKgqC7vgxXPwZVfwMYRXloJvZaBxsHSoQkhhBClksWHgBctWsSoUaMYPnw4AKGhoezcuZO1a9cybdq0bPU3btxoVF69ejXffvstERERDBkypEhiFgVEl0GDf7egPrYDUMCjsX7It0IdS0cmhBBFKq/r+kLZXdtXFCyLJoDp6ekcPXqU6dOnG7ZZWVnh7+9PVFRUntq4f/8+Wq32sescpqWlkZaWZignJSUBoNVq0Wq1+Yhe5Eviv1h9N4q6N34DILPZUHSdPgAbe5B+sYisnwf5ubC8stwXWq0WRclEp8vMtZ6iZBbJv+NZ7WdmKoUaU3x8PJ/99Bf2To9f1xfgQXISE7o2xc3NLU/f1cMxmfrdZv3ZlOsuzHNkZMiLgAXJogng7du3yczMxMPDw2i7h4cHZ8+ezVMbU6dOxdvbG39//xz3z5s3j/fffz/b9gMHDnD69GnTgxb55n7vL5pf/QKbzGS0VnZEVx3BvzwD4fssHZoAwsPDLR2C+K+y2BdJSUlc+scKO8fcE6HUlCTCUy/h7Jx7vYJy5coV7BzvFFpMSUlJ/HvDCrvktFzrpaYkER4ejrOzc56+q4djMvW7BUzui8I8R9S/t3OtI0xj8SHg/Jg/fz6bN28mMjISOzu7HOtMnz6doKAgQ/mff/6hYcOGtG3blurVqxdRpAKATC1WkR+ivrwUAJ2HD/ufGsKzPV7D18bGwsEJrVZLeHg4nTp1wkb6w6LKcl/Ex8cT88tlHJxdc613PymBTm1qPnb0p6BotVq2bdtG9erVcXYtX2gxmXPdeTnG1PoPHwMUSkzmnsOvmjweVJAsmgBWqFABtVrNjRs3jLbfuHEDT0/PXI/95JNPmD9/Pnv37qVJkyaPrWdra4utra2hnJiYCICNjU2Z+4fVohL+1i/ndu2/b2y3Gk1mh2BS9kRIXxQz0h/FR1nsCxsbG1QqNVZW6lzrqVTqIv1+1GpVocZkznXn5RhT6z98TNafCzomc89hbV2i71kVOxZ9ilSj0dCiRQsiIiIM23Q6HREREfj5+T32uAULFjBnzhzCwsJo2bJlUYQq8uPsLgh9Xp/82ZaDl7+Ebh+Dte2TjxVCCCFEgbN4Oh0UFMTQoUNp2bIlrVq1YvHixaSkpBjeCh4yZAiVKlVi3rx5AHz00UfMmjWLTZs2Ub16deLi4gBwcnLCyUmWCStWMtJhbzAcXq4vezeH/uugfHWLhiWEEEKUdRZPAAcMGMCtW7eYNWsWcXFx+Pr6EhYWZngxJDY21uh19xUrVpCenk6/fv2M2gkODiYkJKQoQxe5uXsFtgyHf//Ul58ZB/4hYK2xZFRCCCGEoBgkgADjx49n/PjxOe6LjIw0Kl+5cqXwAxL5c/p7+P4tSLsHdq7QewXU72bpqIQQQgjxX8UiARSlhDYV9syAP1bpy5VbQb+14FrFsnEJIYQQwogkgKJg3LkEW4ZB3HF9+bkJ0HEmqMvWG4xCCCFESSAJoMi/E1vhx4mQngT2bvDSF1C3s6WjEkIIIcRjSAIozKd9AGHT4Oh6fbnqs9B3NZSrZNGwhBBCCJE7SQCFeW5f0A/53jgJqKDNJGg/HdTyV0oIIYQo7uS3tTDdX1/DjkDQpoBjReizEmp1tHRUQgghhMgjSQBF3qXfh12TIfr/9OXqbfRDvs65L9snhBBCiOJFEkCRNzfP6Id8b50FVNB+GrSdDE9Yv1EIIYQQxY8kgCJ3igLRG2HnO5DxAJw89Hf9arS1dGRCCCGEMJMkgOLx0pJhZxAc/1pfrtkB+qwCp4qWjUsIIYQQ+SIJoMhZ3En9kO+dC6Cygg7vwfNB8NC6zEIIIYQomSQBFMYURT+v309TITMNnL2h3xqo9qylIxNCCCFEAZEEUPxPaiLsmAgnv9WXa3fSr+rh+JRFwxJCFA6dTkdCQkKe6rq6umIlIwBClBqSAAq963/ph3zjL4NKDf7B4PeWDPkKUYolJCSwaMcx7Bydc62XmpJEUI9muLm5FVFkQojCJglgWaco8Mdq2P0uZKZDuSrQby1UaWXpyIQQRcDO0RlHF1dLhyGEKGKSAJZlDxLgh7fgzA/6cr1u0GsZOMj/5QshhBClmYzvlVX/HIUv2uqTPysbCJgHr2yS5E8IIUSpMG/ePJ5++mmcnZ1xd3end+/enDt3zqhO+/btUalURp8xY8YY1YmNjaV79+44ODjg7u7O5MmTycjIMKoTGRlJ8+bNsbW1pXbt2qxfv76wLy/fJAEsaxQFopbDmgBIuAqu1WDkbvB7E1QqS0cnhBBCFIj9+/czbtw4Dh8+THh4OFqtls6dO5OSkmJUb9SoUVy/ft3wWbBggWFfZmYm3bt3Jz09nUOHDrFhwwbWr1/PrFmzDHViYmLo3r07HTp0IDo6mokTJ/L666+ze/fuIrtWc8gQcFlyPx6+HwfndunLDV6EF5eAvatFwxJCCCEKWlhYmFF5/fr1uLu7c/ToUdq2/d9qVg4ODnh65rym/Z49ezh9+jR79+7Fw8MDX19f5syZw9SpUwkJCUGj0RAaGkqNGjVYuHAhAA0aNODgwYN8+umnBAQEFN4F5pPcASwr/v5dP+R7bheoNdDtE3j5S0n+hBBClChJSUkkJiYaPmlpaXk67t69ewDZ3mbfuHEjFSpUoHHjxkyfPp379+8b9kVFReHj44OHh4dhW0BAAImJiZw6dcpQx9/f36jNgIAAoqKizLq+oiJ3AEs7nQ6ilkDEbNBlQPka0H89ePtaOjIhhBDCZA0bNjQqBwcHExISkusxOp2OiRMn8txzz9G4cWPD9oEDB1KtWjW8vb05fvw4U6dO5dy5c2zbtg2AuLg4o+QPMJTj4uJyrZOYmMiDBw+wt7c36zoLmySApVnKHdg+Bi7s0Zcb9YGen4Gdi2XjEkIIIcx0+vRpKlWqZCjb2to+8Zhx48Zx8uRJDh48aLR99OjRhj/7+Pjg5eXFCy+8wKVLl6hVq1bBBV0MSQJYWl09BFtHQtK/oLaFrh9Bi2HyoocQQhQBU1dZEXnn7OyMi0veb2SMHz+eHTt2cODAASpXrpxr3datWwNw8eJFatWqhaenJ7///rtRnRs3bgAYnhv09PQ0bHu4jouLS7G9+weSAJY+Oh0cXAT75oKSCU/V0Q/5ejZ+4qFCCCEKhqmrrIiCpygKb731Ft999x2RkZHUqFHjicdER0cD4OXlBYCfnx8ffvghN2/exN3dHYDw8HBcXFwMQ9F+fn7s2rXLqJ3w8HD8/PwK8GoKniSApUnyLdg2Ci7v05ebDIDui8DWybJxCSFEGSSrrFjWuHHj2LRpE99//z3Ozs6GZ/bKlSuHvb09ly5dYtOmTXTr1o2nnnqK48ePExgYSNu2bWnSpAkAnTt3pmHDhgwePJgFCxYQFxfHjBkzGDdunGHoecyYMSxdupQpU6YwYsQIfv75Z7755ht27txpsWvPC0kAS4uYA/Dt65B8A6ztofsn4DtIhnyFEEKUSStWrAD0kz0/bN26dQwbNgyNRsPevXtZvHgxKSkpVKlShb59+zJjxgxDXbVazY4dOxg7dix+fn44OjoydOhQZs+ebahTo0YNdu7cSWBgIJ999hmVK1dm9erVxXoKGJAEsOTTZcKBj2H/R6DooGJ9/ZCvewNLRyaEEEJYjKIoue6vUqUK+/fvf2I71apVyzbE+6j27dtz7Ngxk+KzNEkAS7KkOP2Qb8wBfdn3Nei2ADSOlo1LCCGEEMWaJIAl1aWfYdtoSLkFNo7QYxE0fcXSUQkhhBCiBJAEsKTJzIDIefDLQkAB90b6Id+KdS0dmRBCCCFKCEkAS5J7/+hf9Ig9pC+3GA5d5oFN8Z1nSAghhBDFjySAJcWFcP2Q74N40DhDz8Xg08/SUQkh8siUiYEdHeU5XiFE4ZIEsLjL1MLPc+DXz/Rlzyb6Id+nSvcSNUKUNqZMDPxWgEzcLoQoXJIAFmcJf8PWEXDtv8vQPD0KOn8ANnaWjUsIYRaZGFgIUVxIAlhcnd0F28dCagLYloNeS6BhL0tHJfIpMzMTrVZr6TBypNVqsba2JjU1lczMTEuHU+qkp6fjaAP2Vk/4bm2Kri9MiSk9PZ3U1FRAPzmutbU1KploXogSSxLA4iYjHfaGwOFl+rJ3c+i3FtyevIahKN6Sk5O5du3aEycntRRFUfD09OTvv/+WX+yFQKfT4VdJg0qV+/8AKK4aEhISiqQvTInpzp073L1717DNwcEBLy8vNBpNocUnhCg8kgAWJ3ev6Id8/zmqLz/zJvi/D9byD2xJl5mZybVr13BwcKBixYrFMsHS6XQkJyfj5OSElZWVpcMpdTIyMohPScdKrc61ni4zk/IONjx48KDQ+8KUmNwcNVhbW6MoCunp6dy6dYuYmBjq1Kkjf1+EKIEkASwuTv8A34+HtHtg5wq9V0D9bpaOShQQrVaLoihUrFgRe/viOW2PTqcjPT0dOzs7+YVeCDIyMrDWqlA/IdnKzMzEzk7z3/8Wbl+YFpMt1tb6Xxn29vbY2Nhw9epVw9+ZkkTeyBZCEkDLy0iDPTPg95X6cuWn9UO+rlUtG5coFMXxzp8Q5ijJ/5Mgb2QLIQmgZd25BFuHw/W/9OXnJkDHmaC2sWxcQghRyskb2aKskwTQUk5+Cz9MgPQksHeDl76Aup0tHZUQQgghygBJAIua9gGETYej6/Tlqn7Qdw2Uq2TZuESRM+U5pILi6upaooburly5Qo0aNTh27Bi+vr6WDgeAs2fPMmzYMKKjo6lfvz7R0dFFdu6QkBC2b99epOcUQpROkgAWpdsXYMswuHESUEGbIGj/LqilG8qivD6HVFBSU5II6tEMNze3PB8zbNgwNmzYwLx585g2bZph+/bt23nppZeK7ZQ2hSk4OBhHR0fOnTuHk5NTkZ77nXfe4a233irScwohSifJPIrKX1/DjkDQpoBDBeizEmq/YOmohIWVhOeQ7Ozs+Oijj3jjjTcoX768pcMpEOnp6Ubz1ymKkucJly9dukT37t2pVq2aSecriDuvTk5ORZ50CiFKp5IzFlRSpd+H78fBd6P1yV/1NjD2V0n+RInh7++Pp6cn8+bNe2ydkJCQbEO0ixcvpnr16obysGHD6N27N3PnzsXDwwNXV1dmz55NRkYGkydPxs3NjcqVK7Nu3bps7Z89e5Znn30WOzs7GjduzP79+432nzx5kq5du+Lk5ISHhweDBw/m9u3bhv3t27dn/PjxTJw4kQoVKhAQEGB0fGZmJjcS7hN37wHTZ4ZQpWo1HB0dadqsOV9/t4ObSWncTErDxsaGo0ePMnv2bFQqFSEhITl+H48739nTp3i1by9qelegce1qjB89gjt39HH+Z90amtargU6nM2qrV69ejBgx4rHf8+rVq2nQoAF2dnbUr1+f5cuXG/b169eP8ePHG8oTJ05EpVJx9uxZQJ+Y1q7szoF9PwPw4/ZttPdrSXWP8jSoXon+L3YjJSUlx2ssTnQ6HfHx8U/8PPrdClGWSQJYmG6ehVUd4dj/ASpoNw2GfA/OnpaOTIg8U6vVzJ07lyVLlnDt2rV8tfXzzz/z77//cuDAARYtWkRwcDA9evSgfPny/Pbbb4wZM4Y33ngj23kmT57MpEmTOHbsGH5+fvTs2ZM7d+4A+qH0jh070qxZM44cOUJYWBg3btzg5ZdfNmpjw4YNaDQafv31V0JDQ7PFplKrWbtyBV8sX0LIB/P4+dAfdHihE8MHvczVKzGo1WqOnblEo0aNmDRpEtevX+edd9557LU+er6EhARe7t0dnyZN2R35K199+z23bt5k9NDXAOjZuw934+P59Zf/Jbfx8fGEhYUxaNCgHM+xceNGZs2axYcffsiZM2eYO3cuM2fOZMOGDQC0a9eOyMhIQ/39+/dToUIFw7Y//viDDK2Wlq2f4UbcdcaOHMqrrw3hwO/RbNu5m249e0EJGObPepxi+b6Lj/0s2nGsyJ+5FaI4kwSwMCiKPulb2R5unQEnD33i12E6WOU+4aoQxdFLL72Er68vwcHB+WrHzc2Nzz//nHr16jFixAjq1avH/fv3effdd6lTpw7Tp09Ho9Fw8OBBo+PGjx9P3759adCgAStWrKBcuXKsWbMGgKVLl9KsWTPmzp1L/fr1adasGWvXrmXfvn2cP3/e0EadOnVYsGAB9erVo169ejnGt2LJYsZPmETvfi9Tu05dZs7+kEY+TVi5fCkA7h4eqNVqnJyc8PT0zHU49tHzLV++nMY+TXk3eDZ16tbDp6kvny4L5ddf9nPp4gVcy5enY6fObN+6xdDG1q1bqVChAh06dMjxHMHBwSxcuJA+ffpQo0YN+vTpQ2BgIF988QWgvxN5+vRpbt26xd27dzl9+jQTJkwwJIAHDhygabMWODg4cCMujoyMDLr17EXVatVo0Kgxw0e9gWMJGXLOepzicZ+ietZWiJJCngEsaGnJsHMSHN+sL9dsD31WgZO7RcMSIr8++ugjOnbsmOtdrydp1KiR0bNwHh4eNG78v4l21Wo1Tz31FDdv3jQ6zs/Pz/Bna2trWrZsyZkzZwD466+/2LdvX47J2KVLl6hbty4ALVq0yDW2pMRE4q5f5+ln/Iy2t3rGj1MnTuTxCv/n0fMdP36cQwcPUNO7Qra6V2IuU6t2Hfr0f4V33h5HWpp+LfCvvvqKV155JcfnB1NSUrh06RIjR45k1KhRhu0ZGRmUK1cOgMaNG+Pm5sb+/fvRaDQ0a9aMHj16sGyZvv0DBw7g9/zzADTyaUKbdh3o8OzTtO/oT/uO/vTo9RKupeS5TyGEMUkAC1LcSf3EzrfPg8oKOrwLz0+CEjTthhCP07ZtWwICApg+fTrDhg0z2mdlZZXtjWCtVputDRsb40nOVSpVjttMeVYrOTmZnj178tFHH2Xb5+XlZfhzUS/p9ej5kpOT6RTQlZmz52ar6+6pfyykc9fuKMqb7Nq1i4YNG/LLL7/w6aef5th+cnIyAKtWraJ169ZG+7KWdlOpVLRt25bIyEhsbW1p3749TZo0IS0tjZMnTxIVFcWIMW8Zjvnm+5388VsUkT9HsGblCubNCWFXxAEqV6mSvy9DCFHsSAJYEBQFjq6HsGmQkQrOXvq5/ao/Z+nIhChQ8+fPx9fXN9sQasWKFYmLi0NRFMNydwU5V92hQ4d49tlnAf0drqNHj/Lmm2+SkZGBr68v3333HZUrV8bW1tbs5facXVzw9PLij8NRPPt8G8P23w9H0axFy3xfQ7Nmzdjy7bdUqVbNsKbuo+zs7Oja40W++uorw/fcvHnzHOt6eHjg7e3N5cuXH/uMIOifA1y1ahW2trZ8+OGHWFlZ0bZtWz7++GPS0tJ4uvUzhroqlYpWzzxLq2eeZdLUd2nZuC4/7fieUWPHP7Z9IUTJJAlgfqUmwo6J+pU9AGp3gpdCwTH7MI8Qj0pNSSpR5/Lx8WHQoEF8/vnnRtvbt2/PrVu3WLBgAf369SMsLIyffvoJFxeXfJ8TYOmy5VSsVI06deuxcsVS4u/epUe/V7mZlEb/wSNZtXo1/V5+hfemT8Xd3Z2LFy+yefNmVq9ebbgblhdvvh3Ix/M+oFqNGjRu0pTN//clp04cZ/nq9fm+hrFjx7Jq9WrGjBjCuAlBlC/vRszlS2zftoVFS1YY4nyp/wCGvdqPU6dOMXjw4FzbfP/993n77bcpV64cXbp0IS0tjSNHjnD37l2CgoIAfd8EBgai0Wh4/r/Dve3bt+edd96hZcuWOPz3TuWfR37nl8hI2nV8gQoVK/LnkT+4c/s2derVz/e1CyGKH0kA8+P6X/qJneMvg0oNL8yCZ9+WIV+RJ66urgT1aFbk58yv2bNn8/XXXxtta9CgAcuXL2fu3LnMmTOHvn378s4777By5cp8nw/g3eD3WfbZIk6dOE71mrXY8NVWKrp7AFCpcmV+3LOPObPepVu3bqSlpVGtWjW6dOli8tx7r48ZR2JiIu/PmMbtW7eoW78BGzZvpWat2vm+Bm9vb7b/tJd578/ilZd6kp6eRuUqVeng38kozufbtsPNzY0LFy7w6quv5h7v66/j4ODAxx9/zOTJk3F0dMTHx4eJEyca6vj4+ODq6krdunUNz0m2b9+ezMxM2rVrZ6jn5OzC4UMHWbliKclJiVSuUpXgD+fzQqeAPM+RmBNTVrwpiL+fQoi8kQTQHIoCf6yG3e9CZjq4VIZ+a6Fq6ycfK8R/WVlZmbQqhyWsX78+27bq1auTlpaWbfuYMWMYM2aM0bZ3330317YenqIky5UrV4zOpdVquZmURt+XH58M1axVm9VffoW7s22Ow6s5nScnVlZWvDPtPd6Z9t5j6xw9evSxQ7hPOl/NWrVZu/HrHPc9HMPVq1dJSUnJdgc1JCQk29yDAwcOZODAgbm2Fx8fb7TN19cXRVHIyMjgZpK+L+vWq89X237INTZz5HXFm6yVaoQQRUMSQFOl3oMf3oLT3+vLdbtC7+XgULx/kQshhKWUhBVvhChrJAE0xT9HYctwSLgKVjbQ6X145k0w86FzIYQoSR5eMi8jI8MwvPvwsnpZXF1dC2T5OyFE4ZAEMC8UBX4LhT0zQacF16rQbz1Uzn1eMSFKO1PW0FWr1Wa/oSuKh6wl81RqNRnp6SSlatnzeywpj8z4kzWcW9wfcRCiLJME8Enux8P34+HcTn25QU94cSnYu1o0LCHyIq8Jmilvyj7s4YQg1zgyM/FwdXjis3Mif0zpb3OTcZVajVqtRqdWo1JZYe/oDDpZ4UiIkkb+Nc7N33/oJ3a+9zeoNdD5Q2g1SoZ8hdkenSy5sOUlQctKzswdrstKCHKNw6yWy7asZC4vk2JnJXSm9He+k3HD32X591CIkkgSwJzodBC1BCJmgy4DyteA/uvB29fSkYkSKitBSk9Px97evkjP/aQETZKz4kmn03Hj3n2s1Ln/M/1oQldU/Z2elkqmopCukwRQiJJIEsBHpdyB7WPhwm59uVEf6PkZ2BXMhLaibLK2tsbBwYFbt25hY2NjWDqtsJ+fy8jIICM9HV0uCYEuM5PUVAUrKyvS09NJTU3N893AvLT/8DnMuetUHM+hVqtN7jvTzqEjPT2dvORW+vqpWFtbm9Tfea3/8DEA2vQ0UrVa7ty+xb/3rciUO4BClEhlNgHU6XTZ5sbi7z/0U7wkx4GVBvxn4dp+HFZmPh8lyo68THZrb29PcnIyV65cMax3m3g/HZVV7r9AFZ2Ci4PGrCFanU5HUqoWlerxxyqKjiQ7G1QqFQ8ePMDe3j7PyWZe2n/4HIV1DY+eQ1GUPA23q1QqQ1+Ycg7A5L4z5RyJttY8ePCADCsbrEy4blP629SYDNf9QIuiUvHvfSv+Ts3+9q8QomQoswngvXv3WHswRj85qaLAP0cgNgqUp/UveNTrRuo/dgTduydvshUzpq4skPWLLi/HmFo/65i8Tnabdj+J8Z0bU65cORISEthzKVb/EH0uHqQk8WorL7NWSUhISGDP77mfQ9++J46Ojhw4cIC2bdtiY2NTYO0/fA5XV1d94puYmKf2XVxcSExMNPkcCQkJrI88g62D42Prp91PYVj7Bob6ppwDMLnvTDlH/+YVOH36NNdsq+Dg5JqnmPJ6DlPrP3wMwO7fYrF2KCd3/oQo4cpsAgj/nZzUzgbO7oD4GLDTgEcjqBugf+kjMcHSIebKnESosM8B5Lm+43/XIM3xbmwu5zB1ZQE3N7c8HWNq/YePgbxPdmtjY4OdnR0ajUY/fcYT3qBM0YJGo8HOzu6JbT8qL+d4uP309HTu37+fpwTQ1dXVrGuIj49n6Z5Tef5uzTmHRqMhw8YR21ze1s94pL4p58j6s6kx5fUYGxsb0tPTSbECVQGfw9yYsq77fgY4SvInRIlXLBLAZcuW8fHHHxMXF0fTpk1ZsmQJrVq1emz9LVu2MHPmTK5cuUKdOnX46KOP6Natm+knTvwbTu6H9GSwsoY6ncHLh4J4q60w71JlHWNOImQqcxKhvNZ/K6Cx4RxLdp8slGTrYaYeU9xWLyiKhD8lJYXPfvoLB2fXXOvld9mu4vbdCiFKL1NzjLLC4gng119/TVBQEKGhobRu3ZrFixcTEBDAuXPncHd3z1b/0KFDvPrqq8ybN48ePXqwadMmevfuzZ9//knjxo3zfF6ro+vgTLz+rp/DU9CoNzhWfGz9okjOCvOuUxZTh0LNOUdRJGdlUVEk/AD2TtIXQojSwdQcoyyxeAK4aNEiRo0axfDhwwEIDQ1l586drF27lmnTpmWr/9lnn9GlSxcmT54MwJw5cwgPD2fp0qWEhobm+bxWR9eCfS/wbAJ1/PVDvrkoiuTM3GNMYepQqCheJFEWQoi8MzXHKEssmgCmp6dz9OhRpk+fbthmZWWFv78/UVFROR4TFRVFUFCQ0baAgAC2b9+eY/20tDTS0tIM5Xv37gFwI9WaG+5NsLOrC3/H5nhs6v1krl61ITExkbt373Lv7h2jth5/zFX9Oa5dwc7BKQ/1/3cOU44x9xxPuo6sayjsmGJjVdy+fZvY2Ngiue4nHWOJvigO58iq7+TkRHx8PNczrHF0vmvRmIriHMUxpqxjYmNVJvdFabju4tjfhdkXDx8Dxeu6i2N//2PrAOh/j7u4/G9qNltbW2xtbbMdY06OUaYoFvTPP/8ogHLo0CGj7ZMnT1ZatWqV4zE2NjbKpk2bjLYtW7ZMcXd3z7F+cHCwAshHPvKRj3zkI59S+AkODi6wHKMssfgQcGGbPn260R3D+Ph4atSowcmTJylXrpwFIxNJSUk0bNiQ06dP4+yc+9C6KHzSH8WH9EXxIX1RfNy7d4/GjRsTExNj9IhSTnf/xJNZNAGsUKECarWaGzduGG2/ceMGnp6eOR7j6elpUv3H3RquUqWK0S1kUfSy5oKrVKmS9EUxIP1RfEhfFB/SF8VH1vfv5uaWp74wJ8coS8xb/b2AaDQaWrRoQUREhGGbTqcjIiICPz+/HI/x8/Mzqg8QHh7+2PpCCCGEKHvMyTHKEosPAQcFBTF06FBatmxJq1atWLx4MSkpKYY3doYMGUKlSpWYN28eABMmTKBdu3YsXLiQ7t27s3nzZo4cOcLKlSsteRlCCCGEKGaelGOUZRZPAAcMGMCtW7eYNWsWcXFx+Pr6EhYWhoeHBwCxsbFGE9o+++yzbNq0iRkzZvDuu+9Sp04dtm/fnuc5AG1tbQkODpZnBooB6YviRfqj+JC+KD6kL4oPc/riSTlGWaZSlDysmC6EEEIIIUoNiz4DKIQQQgghip4kgEIIIYQQZYwkgEIIIYQQZYwkgEIIIYQQZUypTACXLVtG9erVsbOzo3Xr1vz++++51t+yZQv169fHzs4OHx8fdu3aVUSRln6m9MWqVato06YN5cuXp3z58vj7+z+x74RpTP3ZyLJ582ZUKhW9e/cu3ADLEFP7IiEhgXHjxuHl5YWtrS1169aVf6sKiKl9sXjxYurVq4e9vT1VqlQhMDCQ1NTUIoq29Dpw4AA9e/bE29sblUrF9u3bn3hMZGQkzZs3x9bWltq1a7N+/fpCj7PUsPRadAVt8+bNikajUdauXaucOnVKGTVqlOLq6qrcuHEjx/q//vqrolarlQULFiinT59WZsyYodjY2CgnTpwo4shLH1P7YuDAgcqyZcuUY8eOKWfOnFGGDRumlCtXTrl27VoRR146mdofWWJiYpRKlSopbdq0UXr16lU0wZZypvZFWlqa0rJlS6Vbt27KwYMHlZiYGCUyMlKJjo4u4shLH1P7YuPGjYqtra2yceNGJSYmRtm9e7fi5eWlBAYGFnHkpc+uXbuU9957T9m2bZsCKN99912u9S9fvqw4ODgoQUFByunTp5UlS5YoarVaCQsLK5qAS7hSlwC2atVKGTdunKGcmZmpeHt7K/Pmzcux/ssvv6x0797daFvr1q2VN954o1DjLAtM7YtHZWRkKM7OzsqGDRsKK8QyxZz+yMjIUJ599lll9erVytChQyUBLCCm9sWKFSuUmjVrKunp6UUVYplhal+MGzdO6dixo9G2oKAg5bnnnivUOMuavCSAU6ZMURo1amS0bcCAAUpAQEAhRlZ6lKoh4PT0dI4ePYq/v79hm5WVFf7+/kRFReV4TFRUlFF9gICAgMfWF3ljTl886v79+2i1WqNFv4V5zO2P2bNn4+7uzsiRI4sizDLBnL744Ycf8PPzY9y4cXh4eNC4cWPmzp1LZmZmUYVdKpnTF88++yxHjx41DBNfvnyZXbt20a1btyKJWfyP/P7OH4uvBFKQbt++TWZmZrYZvj08PDh79myOx8TFxeVYPy4urtDiLAvM6YtHTZ06FW9v72w/4MJ05vTHwYMHWbNmDdHR0UUQYdlhTl9cvnyZn3/+mUGDBrFr1y4uXrzIm2++iVarJTg4uCjCLpXM6YuBAwdy+/Ztnn/+eRRFISMjgzFjxvDuu+8WRcjiIY/7/Z2YmMiDBw+wt7e3UGQlQ6m6AyhKj/nz57N582a+++477OzsLB1OmZOUlMTgwYNZtWoVFSpUsHQ4ZZ5Op8Pd3Z2VK1fSokULBgwYwHvvvUdoaKilQytzIiMjmTt3LsuXL+fPP/9k27Zt7Ny5kzlz5lg6NCFMUqruAFaoUAG1Ws2NGzeMtt+4cQNPT88cj/H09DSpvsgbc/oiyyeffML8+fPZu3cvTZo0KcwwywxT++PSpUtcuXKFnj17GrbpdDoArK2tOXfuHLVq1SrcoEspc342vLy8sLGxQa1WG7Y1aNCAuLg40tPT0Wg0hRpzaWVOX8ycOZPBgwfz+uuvA+Dj40NKSgqjR4/mvffeM1q7XhSux/3+dnFxkbt/eVCq/qZqNBpatGhBRESEYZtOpyMiIgI/P78cj/Hz8zOqDxAeHv7Y+iJvzOkLgAULFjBnzhzCwsJo2bJlUYRaJpjaH/Xr1+fEiRNER0cbPi+++CIdOnQgOjqaKlWqFGX4pYo5PxvPPfccFy9eNCThAOfPn8fLy0uSv3wwpy/u37+fLcnLSswVRSm8YEU28vs7nyz9FkpB27x5s2Jra6usX79eOX36tDJ69GjF1dVViYuLUxRFUQYPHqxMmzbNUP/XX39VrK2tlU8++UQ5c+aMEhwcLNPAFBBT+2L+/PmKRqNRtm7dqly/ft3wSUpKstQllCqm9sej5C3ggmNqX8TGxirOzs7K+PHjlXPnzik7duxQ3N3dlQ8++MBSl1BqmNoXwcHBirOzs/LVV18ply9fVvbs2aPUqlVLefnlly11CaVGUlKScuzYMeXYsWMKoCxatEg5duyYcvXqVUVRFGXatGnK4MGDDfWzpoGZPHmycubMGWXZsmUyDYwJSl0CqCiKsmTJEqVq1aqKRqNRWrVqpRw+fNiwr127dsrQoUON6n/zzTdK3bp1FY1GozRq1EjZuXNnEUdcepnSF9WqVVOAbJ/g4OCiD7yUMvVn42GSABYsU/vi0KFDSuvWrRVbW1ulZs2ayocffqhkZGQUcdSlkyl9odVqlZCQEKVWrVqKnZ2dUqVKFeXNN99U7t69W/SBlzL79u3L8XdA1vc/dOhQpV27dtmO8fX1VTQajVKzZk1l3bp1RR53SaVSFLlnLYQQQghRlpSqZwCFEEIIIcSTSQIohBBCCFHGSAIohBBCCFHGSAIohBBCCFHGSAIohBBCCFHGSAIohBBCCFHGSAIohBBCCFHGSAIohCj2hg0bRu/evQ3l9u3bM3HixCKPIzIyEpVKRUJCQpGfWwghCpIkgEIIswwbNgyVSoVKpUKj0VC7dm1mz55NRkZGoZ9727ZtzJkzJ091izppq169uuF7cXBwwMfHh9WrVxfJuYUQIq8kARRCmK1Lly5cv36dCxcuMGnSJEJCQvj4449zrJuenl5g53Vzc8PZ2bnA2itos2fP5vr165w8eZLXXnuNUaNG8dNPP1k6LCGEMJAEUAhhNltbWzw9PalWrRpjx47F39+fH374AfjfsO2HH36It7c39erVA+Dvv//m5ZdfxtXVFTc3N3r16sWVK1cMbWZmZhIUFISrqytPPfUUU6ZM4dEVKx8dAk5LS2Pq1KlUqVIFW1tbateuzZo1a7hy5QodOnQAoHz58qhUKoYNGwaATqdj3rx51KhRA3t7e5o2bcrWrVuNzrNr1y7q1q2Lvb09HTp0MIozN87Oznh6elKzZk2mTp2Km5sb4eHhJnyzQghRuCQBFEIUGHt7e6M7fREREZw7d47w8HB27NiBVqslICAAZ2dnfvnlF3799VecnJzo0qWL4biFCxeyfv161q5dy8GDB4mPj+e7777L9bxDhgzhq6++4vPPP+fMmTN88cUXODk5UaVKFb799lsAzp07x/Xr1/nss88AmDdvHl9++SWhoaGcOnWKwMBAXnvtNfbv3w/oE9U+ffrQs2dPoqOjef3115k2bZpJ34dOp+Pbb7/l7t27aDQak44VQohCpQghhBmGDh2q9OrVS1EURdHpdEp4eLhia2urvPPOO4b9Hh4eSlpamuGY//znP0q9evUUnU5n2JaWlqbY29sru3fvVhRFUby8vJQFCxYY9mu1WqVy5cqGcymKorRr106ZMGGCoiiKcu7cOQVQwsPDc4xz3759CqDcvXvXsC01NVVxcHBQDh06ZFR35MiRyquvvqooiqJMnz5dadiwodH+qVOnZmvrUdWqVVM0Go3i6OioWFtbK4Di5uamXLhw4bHHCCFEUbO2bPophCjJduzYgZOTE1qtFp1Ox8CBAwkJCTHs9/HxMbrz9ddff3Hx4sVsz++lpqZy6dIl7t27x/Xr12ndurVhn7W1NS1btsw2DJwlOjoatVpNu3bt8hz3xYsXuX//Pp06dTLanp6eTrNmzQA4c+aMURwAfn5+eWp/8uTJDBs2jOvXrzN58mTefPNNateunef4hBCisEkCKIQwW4cOHVixYgUajQZvb2+srY3/SXF0dDQqJycn06JFCzZu3JitrYoVK5oVg729vcnHJCcnA7Bz504qVapktM/W1tasOB5WoUIFateuTe3atdmyZQs+Pj60bNmShg0b5rttIYQoCPIMoBDCbI6OjtSuXZuqVatmS/5y0rx5cy5cuIC7u7shQcr6lCtXjnLlyuHl5cVvv/1mOCYjI4OjR48+tk0fHx90Op3h2b1HZd2BzMzMNGxr2LAhtra2xMbGZoujSpUqADRo0IDff//dqK3Dhw8/8RofVaVKFQYMGMD06dNNPlYIIQqLJIBCiCIzaNAgKlSoQK9evfjll1+IiYkhMjKSt99+m2vXrgEwYcIE5s+fz/bt2zl79ixvvvlmrnP4Va9enaFDhzJixAi2b99uaPObb74BoFq1aqhUKnbs2MGtW7dITk7G2dmZd955h8DAQDZs2MClS5f4888/WbJkCRs2bABgzJgxXLhwgcmTJ3Pu3Dk2bdrE+vXrzbruCRMm8OOPP3LkyBGzjhdCiIImCaAQosg4ODhw4MABqlatSp8+fWjQoAEjR44kNTUVFxcXACZNmsTgwYMZOnQofn5+ODs789JLL+Xa7ooVK+jXrx9vvvkm9evXZ9SoUaSkpABQqVIl3n//faZNm4aHhwfjx48HYM6cOcycOZN58+bRoEEDunTpws6dO6lRowYAVatW5dtvv2X79u00bdqU0NBQ5s6da9Z1N2zYkM6dOzNr1iyzjhdCiIKmUh73ZLUQQgghhCiV5A6gEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZIwmgEEIIIUQZ8/+6JE7TjNy5rQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Universal Metric of FSRS: 0.0106\n",
      "Universal Metric of SM2: 0.0838\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sm2(history):\n",
    "    ivl = 0\n",
    "    ef = 2.5\n",
    "    reps = 0\n",
    "    for delta_t, rating in history:\n",
    "        delta_t = delta_t.item()\n",
    "        rating = rating.item() + 1\n",
    "        if rating > 2:\n",
    "            if reps == 0:\n",
    "                ivl = 1\n",
    "                reps = 1\n",
    "            elif reps == 1:\n",
    "                ivl = 6\n",
    "                reps = 2\n",
    "            else:\n",
    "                ivl = ivl * ef\n",
    "                reps += 1\n",
    "        else:\n",
    "            ivl = 1\n",
    "            reps = 0\n",
    "        ef = max(1.3, ef + (0.1 - (5 - rating) * (0.08 + (5 - rating) * 0.02)))\n",
    "        ivl = max(1, round(ivl+0.01))\n",
    "    return ivl\n",
    "\n",
    "dataset['sm2_interval'] = dataset['tensor'].map(sm2)\n",
    "dataset['sm2_p'] = np.exp(np.log(0.9) * dataset['delta_t'] / dataset['sm2_interval'])\n",
    "cross_comparison = dataset[['sm2_p', 'p', 'y']].copy()\n",
    "\n",
    "R_Metric = mean_squared_error(cross_comparison['y'], cross_comparison['sm2_p'], squared=False) - mean_squared_error(cross_comparison['y'], cross_comparison['p'], squared=False)\n",
    "print(\"R_Metric: \", R_Metric)\n",
    "plot_brier(dataset['sm2_p'], dataset['y'], bins=40)\n",
    "plt.show()\n",
    "\n",
    "plt.figure(figsize=(6, 6))\n",
    "\n",
    "cross_comparison['SM2_B-W'] = cross_comparison['sm2_p'] - cross_comparison['y']\n",
    "cross_comparison['SM2_bin'] = cross_comparison['sm2_p'].map(lambda x: round(x, 1))\n",
    "cross_comparison['FSRS_B-W'] = cross_comparison['p'] - cross_comparison['y']\n",
    "cross_comparison['FSRS_bin'] = cross_comparison['p'].map(lambda x: round(x, 1))\n",
    "\n",
    "plt.axhline(y = 0.0, color = 'black', linestyle = '-')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='SM2_bin').agg({'y': ['mean'], 'FSRS_B-W': ['mean'], 'p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of FSRS: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['p', 'mean'], sample_weight=cross_comparison_group['p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['p', 'percent'] = cross_comparison_group['p', 'count'] / cross_comparison_group['p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['FSRS_B-W', 'mean'], s=cross_comparison_group['p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['FSRS_B-W', 'mean'], label='FSRS by SM2')\n",
    "\n",
    "cross_comparison_group = cross_comparison.groupby(by='FSRS_bin').agg({'y': ['mean'], 'SM2_B-W': ['mean'], 'sm2_p': ['mean', 'count']})\n",
    "print(f\"Universal Metric of SM2: {mean_squared_error(cross_comparison_group['y', 'mean'], cross_comparison_group['sm2_p', 'mean'], sample_weight=cross_comparison_group['sm2_p', 'count'], squared=False):.4f}\")\n",
    "cross_comparison_group['sm2_p', 'percent'] = cross_comparison_group['sm2_p', 'count'] / cross_comparison_group['sm2_p', 'count'].sum()\n",
    "plt.scatter(cross_comparison_group.index, cross_comparison_group['SM2_B-W', 'mean'], s=cross_comparison_group['sm2_p', 'percent'] * 1024, alpha=0.5)\n",
    "plt.plot(cross_comparison_group['SM2_B-W', 'mean'], label='SM2 by FSRS')\n",
    "\n",
    "plt.legend(loc='lower center')\n",
    "plt.grid(linestyle='--')\n",
    "plt.title(\"SM2 vs. FSRS\")\n",
    "plt.xlabel('Predicted R')\n",
    "plt.ylabel('B-W Metric')\n",
    "plt.xlim(0, 1)\n",
    "plt.xticks(np.arange(0, 1.1, 0.1))\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "fsrs4anki",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
